A Prediction System Based on Fuzzy Logic

Size: px
Start display at page:

Download "A Prediction System Based on Fuzzy Logic"

Transcription

1 Proceedngs of the World Congress on Engneerng and Comuter Scence 2008 WCECS 2008, October 22-24, 2008, San Francsco, USA A Predcton System Based on Fuzzy Logc Vadeh.V,Monca.S, Mohamed Shek Safeer.S, Deeka.M 4, Sangeetha.S ABSTRACT: The man objectve of the aer s to buld a redcton system to redct the future occurrence of an event. Fuzzy logc, among the varous avalable Artfcal Intellgence technques, emerges as an advantageous technque n redctng future events. Subjectve and Objectve modelng are two tyes of fuzzy modelng. Objectve tye fuzzy modelng s used to buld the redcton system. It s a combnaton of a clusterng algorthm and fuzzy system dentfcaton whch roves effectve n mrovng the effcency of the redcton. To tran the redcton system, hstorcal data s obtaned from the web. Data secfc to the desred alcaton s obtaned and s recorded. Ths recorded nformaton s subjectvely reasoned to develo contanng only the necessary nuts to the redcton system. The subtractve clusterng algorthm s used for ts comutatonal advantages and fuzzy rules are formed usng system dentfcaton technque. Stock markets are ecellent eamles where ths redcton system can be aled and the ossblty of a rse or a fall n the market rces s redcted. The entre redcton system s realzed usng Java. Keywords: Predcton, Data modelng, Subtractve clusterng, System dentfcaton, Fuzzy logc. I. INTRODUCTION Predcton of an event requres vague, merfect and uncertan knowledge [9]. Comlety n a redcton system s ts ntrnsc characterstc. Varous Artfcal Intellgence (AI) technques have been utlzed n realsng a redcton system [2]. The AI based redcton models can be classfed nto four grous: models based on neural networks, fuzzy logc, genetc algorthm and eert systems. Such redcton systems lay mortant roles n several organsatonal decsons, of whch the stock market s a vvd eamle. Rules whch determne market behavour have been elcted from raw data by AI methods. As stock market redcton nvolves mrecse concets and mrecse reasonng, fuzzy logc s a natural choce for knowledge reresentaton [2]. The Web, wth ts boundless nformaton, acts as a source of hstorcal haenngs of events. Relevant data concernng the alcaton s arsed and fltered and used to tran the redcton system. Manuscrt receved Jul 2, V.Vadeh s a faculty and Monca.S, Mohamed Shek Safeer.S, Deeka.M, Sangeetha.S are students of Deartment of Electroncs Engneerng, Madras Insttute of Technology, Anna Unversty, Chenna, Taml Nadu, Inda (emal d : vadehvjay@gmal.com) Earler, redcton systems were bult wth rules formed manually. Rules became comlcated wth ncrease n the number of nuts and redctng an event grew tedous. Engneerng hels buld a redcton system that could adat to the ncreasng number of nuts and frame rules accordngly. The accuracy and seed obtaned s sueror to manual redcton schemes. Objectve fuzzy modellng [] used to buld the redcton system requres numercal nuts. The IF-THEN rules formed have vague redcates n ther antecedent art whle the consequent art s a lnear or quadratc combnaton of the antecedent varables. Snce the consequent arts of rules are crs values rather than vague and fuzzy ones, there s no need to defuzzfy the outut. Ths characterstc of the objectve fuzzy modelng technque favours t over several other fuzzy modelng technques and s utlzed to mrove the redcton effcency. The objectve tye fuzzy modellng has ecellent learnng caabltes and requres less comutatonal effort. Subtractve clusterng technque used oerates on raw numercal data. Increasng the number of nuts affects the redcton system only to a small etent. Further ths clusterng technque rovdes smlar degree of accuracy and robustness together wth lesser comutatonal comlety as comared to varous other clusterng technques. These advantages along wth the characterstc that no searate defuzzfcaton s requred, makes ths redcton faster than several revous systems. Secton II resents an overvew of the redcton system and the nherent concets. Secton III dscusses the fuzzy modelng technque n detal wth the underlyng mathematcal foundatons. Secton IV dscusses the mlementaton results of the technque used and analyses the results. Secton V gves a bref concluson. II. PREDICTION SYSTEM Predctng a system s usually done by learnng from the ast for whch hstorcal data s obtaned and analyzed to study the resultng attern n the market [3]. The archtecture of the redcton system based on fuzzy logc s gven n Fg. Predctng any event requres knowledge about ast erformance. Data from the ast s used manly to learn the atterns that ested. Hstorcal data rovdes nformaton on the secfc attern of ISBN: WCECS 2008

2 Proceedngs of the World Congress on Engneerng and Comuter Scence 2008 WCECS 2008, October 22-24, 2008, San Francsco, USA Hstorcal data 2-D Mang learnng the data. Learnng from the ast rovdes knowledge about future to some etent. Fg Block Dagram for Fuzzy Based Predcton System Web feeds rovde users wth frequently udated content. The block dagram to obtan nuts to the redcton system from web feeds s shown n fg 2. Web ages relatng to the secfc alcaton are dentfed. In ths case, stock market related web ages are all dentfed. The ayload from the chosen web ages s obtaned usng a feed reader. The ayload could be obtaned n any desred format. Web Feeds Densty Functon Feed Reader Recent Data Data Clusterng Parser Predcton System Hstorcal Data Recent data System Identfcaton Predcted Outut Database Predcted Outut Fg 2 Block dagram showng web nuts to redcton system XML format s wdely used to create most web ages [0]. The ayload could hence be obtaned n the XML format. The Document Object Model (DOM) s the foundaton of Etensble Mark-u Language, or XML. XML documents have a herarchy of nformatonal unts called nodes []. The XML DOM (Document Object Model) defnes a standard way for accessng and manulatng XML documents. The DOM resents an XML document as a tree structure, wth elements, attrbutes, and tet as nodes. Informaton from the web ages s obtaned by arsng the ml document. A database s formed wth the arsed data. An analyss of the database rovdes a cture of the varatons n the market due to the numerous avalable factors rangng from economcal to oltcal factors. All these factors can be fnally dstlled nto one market varable, the stock market rce. Stock rces for a day are of varous categores lke oenng rce, hgh, low, closng rce, etc [7]. Of these, oen and close rces are consdered and used to roduce a 2-D mang [6]. The ast values of oen and close rces of a artcular stock s recorded for a sequence of days and stored n database to tran the redcton system. A defnte number of such ars of values corresondng to a set of contnuous days tran the system to learn the attern of behavour of the market over a defnte erod. III. FUZZY MODELING The roblem of fuzzy system dentfcaton s the roblem of elctng IF-THEN rules from raw nut and outut data. Ths roceeds through two stes: ) Clusterng 2) Secfcaton of nut-outut relatons (IF- THEN rules) Clusterng algorthms are used etensvely not only to organze and categorze data, but are also useful for data comresson and model constructon [4]. By fndng smlartes n data, one can reresent smlar data wth fewer symbols. The densty functon for a data ont s defned as the measure of otental for that data ont. It s estmated based on the dstance of ths data ont from all other data onts, Therefore, a data ont lyng n a hea of other data onts wll have a hgh chance of beng a cluster centre, whle a data ont whch s located n an area of dffused and not concentrated data onts wll have a low chance of beng a cluster centre. The rocess of cluster centre determnaton nvolves determnng the otentals of every data ont consdered. The data ont wth the hghest otental s chosen as the frst cluster centre. The subsequent cluster centres are found by frst revsng the otental of data onts to cancel the effect of the revous cluster centres found. Ths rocess s a selftermnatng one, that s, when the revsed otentals of data onts are not suffcent for the artcular data ont to become a cluster centre, the cluster centre determnaton termnates. In our case, a set of two clusters s formed - one to denote the hgher range n the rce values and the other to denote the lower range of rces. The system s now sad to be traned. If a set of recent data values s now resented to ths system, the attern s studed and the ossblty of a rse or a fall s redcted along wth the net ossble value for the market varable, the rce. The recent data values are ntally rocessed, ther membersh wth each of the clusters formed earler s determned. Each of the data onts receved recently s laced n the cluster where ts membersh wth that cluster s the hghest. ISBN: WCECS 2008

3 Proceedngs of the World Congress on Engneerng and Comuter Scence 2008 WCECS 2008, October 22-24, 2008, San Francsco, USA Recent Membersh Functon Fuzzy IF- THEN rules Outut near the frst cluster beng selected as the net cluster centre. After revsng the otental of al data onts, the data ont wth the mamum otental wll be selected as the net cluster centre. The otental of data onts n the frst ste s measured as [8]: Cluster Centre e α n = j 2 () j = Fg 3 Block Dagram for System Identfcaton Each cluster centre corresonds to fuzzy rule and the cluster dentfed by the eonental membersh functon reresents the antecedent of ths rule. The rule checks f the nut s the same as the eonental membersh functon of cluster I and f so, then the outut s set to the quadratc combnaton of the nut varables. A hgher number of data onts laced n one cluster ncreases the favourablty for that cluster, that s, f a set of recent nuts has had a larger number of rces n the hgher range, then the ossblty s that the rces are lkely to rse n the near future. The net mmedate value of the rce s found usng equaton 7.. Subtractve Clusterng Clusterng s a rocess n whch data are laced nto grous or clusters, such that data n a gven cluster tend to be smlar to each other, and data n dfferent clusters tend to be dssmlar. When the clusterng estmaton s aled to a set of nutoutut data, each cluster centre can be consdered as a fuzzy rule that descrbes the characterstc behavour of the system. Each cluster centre corresonds to fuzzy rule, and the cluster dentfed reresents the antecedent of ths rule. Ths ste forms the system dentfcaton. Subtractve clusterng s a technque for automatcally generatng fuzzy nference systems by detectng clusters n nut-outut tranng data. Subtractve clusterng, unlke mountan clusterng whch consders ntersecton of grd Lnes, consders each data ont as a otental cluster centre. The measure of otental for a data ont s estmated based on the dstance of ths data ont from all other data onts. Therefore, a data ont lyng n a hea of other data onts wll have a hgh chance of beng a cluster centre, whle a data ont whch s located n an area of dffused and not concentrated data onts wll have a low chance of beng a cluster centre. After measurng the otental of every data ont, the data ont wth the greatest otental value s selected as the frst cluster centre. To fnd the net cluster centre, otentals of data onts must be revsed. For each data ont, an amount roortonal to ts dstance to the frst cluster centre wll be subtracted. Ths reduces the chance of a data ont α = 4 where 2 r a and s the th data ont and r a s a vector whch conssts of ostve constants and reresents the hyer shere cluster radus n data sace. The constant r a s effectvely the radus defnng a neghbourhood; data onts outsde ths radus have lttle nfluence on the otental. The otental whch has been calculated through Equaton for a gven ont, s a functon of that ont's dstance to all other onts, and the data ont whch corresonds to mamum otental value s the frst cluster centre. Let denotes the mamum otental, f denotes the frst cluster centre corresondng to, where U n = = U (2) denotes the mamum of al s To revse the otental values and select the net cluster, the followng formula s suggested. 2 j e β 4 where β = 2 = (3) r b and r b s a vector whch conssts of ostve constants and s called the hyer shere enalty radus. The constant r b s effectvely the radus defnng the neghbourhood whch wll have measurable reductons n otental. To avod cluster centres beng close to each other, r b must be greater than r a. A desrable relaton s as follows [8]: r b =.5r a (4) ISBN: WCECS 2008

4 Proceedngs of the World Congress on Engneerng and Comuter Scence 2008 WCECS 2008, October 22-24, 2008, San Francsco, USA Subtractve clusterng can be used as a standalone aromate clusterng algorthm n order to estmate number of clusters and ther locatons. 2. Fuzzy Rule Formaton When the clusterng estmaton s aled to a set of nut-outut data, each cluster centre can be consdered as a fuzzy rule that descrbes the characterstc behavour of the system. Theoretcally, a system wth multle nuts and multle oututs can be reduced to several multle nuts but sngle outut systems (MISO). Therefore, the fuzzy rule of a MIMO system can also be resented as a set of rules wth mult-antecedent and sngle-consequent such that for a system wth n outut, each multconsequent rule s broken nto n sngle-consequent rules. Consderng data n an n-dmensonal sace, where the frst k dmensons corresond to nut varables and (n-k) dmensons corresond to outut varables, the clusterng estmaton on ths data sace dvdes the data nto fuzzy clusters that overla wth each other. The deendency of each data vector can be defned by a membersh grade n [0, ]. The data vector wth membersh grade, one, s called the cluster centre. The membersh grade of each data vector s defned as follows: μ e α 2 ( ) = (5) where s the nut vector. Each cluster centre c corresonds to, and the fuzzy rule cluster dentfed above by the eonental membersh functon reresents the antecedent of ths rule. If A notfes the eonental membersh functon of cluster, then rule can be reresented as: IF X s A THEN Y s B where X s the nut varables vector, Y s the th outut varable and B s a sngleton defned as a lnear or quadratc combnaton of nut varables. When B s defned as a lnear combnaton, the model s called a frst order model and when B s a quadratc combnaton, the model s called a second order model. For the frst order model that we are concerned about n ths work, B s gven as follows: where, B = N j = j j + (6) 0 j s the coeffcent of j n rule. The fuzzy IF-THEN rules for the frst order model would be as follows (genercally): IF X s A THEN Y (X) = N j = j j + 0 For a gven X 0 the outut of the model y 0, s comuted as: y s μ = = 0 s = ( ) ( ) μ 0 0 ( ) Y 0 (7) The system s thus formed. And the redcted outut of the system s gven by equaton 7. IV. RESULTS Stock rces for fve organsatons are consdered and the redcton system s aled to each organsaton. The redctons made for the organsatons have an accuracy of about 80%. The results for one of the organsatons consdered are elaborated. The ml fle obtaned from the feed reader s gven as nut to the DOM arser. Hstorcal data comrsng of oenng rce and closng rce of a secfc organzaton as collected from the data sheet of a comany for a secfc erod s shown n Table. CLOSING PRICE HISTORICAL DATA OPENING PRICE Fg 4 Hstorcal Data Cluster centres are calculated usng subtractve clusterng algorthm. The two cluster centres that were obtaned for the ast values that were consdered are shown n Fg 5. The data ont at the lower range n Fg 5 ndcates the cluster centre for a FALL n the rce values. ISBN: WCECS 2008

5 Proceedngs of the World Congress on Engneerng and Comuter Scence 2008 WCECS 2008, October 22-24, 2008, San Francsco, USA Table Data Sheet Date Oen Close Date Oen Close ACTUAL Vs PREDICTED 9/26/ /9/ /25/ /8/ /24/ /7/ /2/ /6/ /20/ /3/ CLOSING PRICE DAY ACTUAL PREDICTED 9/9/ /2/ /8/ // /7/ /3/ Fg 6 Actual Vs Predcted Curves CLUSTER CENTERS 9/4/ /30/ /3/ /27/ /2/ /26/ // /25/ /0/ /24/ /7/ /23/ /6/ /20/ /5/ /9/ /4/ /8/ /3/ /7/ /30/ /6/ /29/ /3/ /28/ /2/ /27/ // /24/ /0/ /23/ /9/ /22/ /6/ /2/ /5/ /20/ /3/ /7/ /2/ /6/ /29/ /5/ /28/ /4/ /27/ /3/ /26/ OPENING PRICE Fg 5 Cluster Centres Smlarly, the data ont at the hgher range ndcates the cluster centre for a RISE n the rce values. We have consdered 64 values of oenng and close rces and have lotted the data onts as shown n Fg 4.The recent data gven to the traned system roduces a redcted outut whch s ndcated as the PREDICTED curve n Fg 6. Ths curve s lotted n comarson wth the actual outut, ndcated by the ACTUAL curve n Fg 6. V. CONCLUSION A subtractve clusterng based fuzzy system dentfcaton method s used to successfully model a general redcton system that can redct future events by takng samles of ast events. Hstorcal data s obtaned and s used to tran the redcton system. Recent data are gven as nut to the redcton system. All data are secfc to the alcaton at hand. The system, that s develoed usng Java, s tested n one of the many areas where redcton lays an mortant role, the stock market. Prces of revous sessons of the market are taken as the otental nuts. When recent data are gven to the traned system, t redcts the ossblty of a rse or a fall along wth the net ossble value of data. The accuracy obtaned s about 80%. The redcton model that we have desgned s traned by daly market rce data. It can also be used as a weekly or a monthly redctor. Ths serves as one ossble area of ISBN: WCECS 2008

6 Proceedngs of the World Congress on Engneerng and Comuter Scence 2008 WCECS 2008, October 22-24, 2008, San Francsco, USA future work. Further, the nuts from the XML document and the fuzzy rules can be ntegrated to serve a real tme alcaton. REFERENCES [] Alaa Sheta, Software Effort Estmaton and Stock Market Predcton Usng Takag-Sugeno Fuzzy Models IEEE Internatonal Conference on Fuzzy System,.7-78, July [2] Chu S.C. And Km H.S, "Automatc knowledge generaton from the stock market data", Proceedngs of 93 Korea Jaan jont conference on eert systems, , 993. [3] Justn Wolfers, Erc Ztzewtz, Predcton markets n theory and ractce, natonal bureau of economc research,.-, March [4] Khaled Hammouda, Prof. Fakhreddne Karray, A comaratve study of data clusterng technques.-, March [5] R. Babuska, J. A. Roubos, and H. B. Verbruggen, Identfcaton of MIMO systems by nut-outut TS fuzzy models, n Proceedngs of Fuzzy-IEEE 98, Anchorage, Alaska, 998. [6] R. J. Van Eyden, Alcaton of Neural Networks n the Forecastng of Share Prces Fnance and Technology Publshng, 996. [7] Yke Hemstra, A Stock Market Forecastng Suort System Based on Fuzzy Logc, Proceedngs of the Twenty-Seventh Annual Hawa Internatonal Conference on System, Scences, IEEE, ,994. [8] Chu, S. L.; 994, "Fuzzy model dentfcaton based on cluster estmaton", Journal of Intellgent and Fuzzy Systems, 2, John Wley & Sons, [9] Avalable onlne (Process modellng) htt:// m. [0] Avalable onlne: [] Avalable onlne: ISBN: WCECS 2008

Forecasting the Direction and Strength of Stock Market Movement

Forecasting the Direction and Strength of Stock Market Movement Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems

More information

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network 700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School

More information

Real-Time Traffic Signal Intelligent Control with Transit-Priority

Real-Time Traffic Signal Intelligent Control with Transit-Priority 738 JOURNAL OF SOFTWARE, VOL. 7, NO. 8, AUGUST 202 Real-Tme Traffc Sgnal Intellgent ontrol wth Transt-Prorty Xanyan Kuang School of vl Engneerng and Transortaton, South hna Unversty of Technology, GuangZhou,

More information

Analysis and Modeling of Buck Converter in Discontinuous-Output-Inductor-Current Mode Operation *

Analysis and Modeling of Buck Converter in Discontinuous-Output-Inductor-Current Mode Operation * Energy and Power Engneerng, 3, 5, 85-856 do:.436/ee.3.54b63 Publshed Onlne July 3 (htt://www.scr.org/journal/ee) Analyss and Modelng of Buck Converter n Dscontnuous-Outut-Inductor-Current Mode Oeraton

More information

A New Technique for Vehicle Tracking on the Assumption of Stratospheric Platforms. Department of Civil Engineering, University of Tokyo **

A New Technique for Vehicle Tracking on the Assumption of Stratospheric Platforms. Department of Civil Engineering, University of Tokyo ** Fuse, Taash A New Technque for Vehcle Tracng on the Assumton of Stratosherc Platforms Taash FUSE * and Ehan SHIMIZU ** * Deartment of Cvl Engneerng, Unversty of Toyo ** Professor, Deartment of Cvl Engneerng,

More information

Vision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION

Vision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION Vson Mouse Saurabh Sarkar a* a Unversty of Cncnnat, Cncnnat, USA ABSTRACT The report dscusses a vson based approach towards trackng of eyes and fngers. The report descrbes the process of locatng the possble

More information

www.engineerspress.com Neural Network Solutions for Forward Kinematics Problem of Hybrid Serial-Parallel Manipulator

www.engineerspress.com Neural Network Solutions for Forward Kinematics Problem of Hybrid Serial-Parallel Manipulator www.engneersress.com World of Scences Journal ISSN: 307-307 Year: 03 Volume: Issue: 8 Pages: 48-58 Aahmad Ghanbar,, Arash ahman Deartment of Mechancal Engneerng, Unversty of Tabrz, Tabrz, Iran School of

More information

ADOPTION OF BIG DATA ANALYTICS IN HEALTHCARE: THE EFFICIENCY AND PRIVACY

ADOPTION OF BIG DATA ANALYTICS IN HEALTHCARE: THE EFFICIENCY AND PRIVACY ADOPTION OF BIG DATA ANALYTICS IN HEALTHCARE: THE EFFICIENCY AND PRIVACY He L, School of Economc Informaton Engneerng, Southwestern Unversty of Fnance and Economcs, Chengdu, Chna, olverlhe@gmalcom Jng

More information

Applied Research Laboratory. Decision Theory and Receiver Design

Applied Research Laboratory. Decision Theory and Receiver Design Decson Theor and Recever Desgn Sgnal Detecton and Performance Estmaton Sgnal Processor Decde Sgnal s resent or Sgnal s not resent Nose Nose Sgnal? Problem: How should receved sgnals be rocessed n order

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

An Interest-Oriented Network Evolution Mechanism for Online Communities

An Interest-Oriented Network Evolution Mechanism for Online Communities An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,

More information

Learning User's Scheduling Criteria in a Personal Calendar Agent!

Learning User's Scheduling Criteria in a Personal Calendar Agent! Learnng User's Schedulng Crtera n a Personal Calendar Agent! Shh-ju Ln and Jane Yung-jen Hsu Deartment of Comuter Scence and Informaton Engneerng Natonal Tawan Unversty 1 Sec 4 Roosevelt Road, Tae, 106

More information

A DATA MINING APPLICATION IN A STUDENT DATABASE

A DATA MINING APPLICATION IN A STUDENT DATABASE JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES JULY 005 VOLUME NUMBER (53-57) A DATA MINING APPLICATION IN A STUDENT DATABASE Şenol Zafer ERDOĞAN Maltepe Ünversty Faculty of Engneerng Büyükbakkalköy-Istanbul

More information

A NEW ACTIVE QUEUE MANAGEMENT ALGORITHM BASED ON NEURAL NETWORKS PI. M. Yaghoubi Waskasi MYaghoubi@ece.ut.ac.ir. M. J. Yazdanpanah Yazdan@ut.ac.

A NEW ACTIVE QUEUE MANAGEMENT ALGORITHM BASED ON NEURAL NETWORKS PI. M. Yaghoubi Waskasi MYaghoubi@ece.ut.ac.ir. M. J. Yazdanpanah Yazdan@ut.ac. A NEW ACTIVE QUEUE MANAGEMENT ALGORITHM BASED ON NEURAL NETWORKS M. Yaghoub Waskas MYaghoub@ece.ut.ac.r M. J. Yazdananah Yazdan@ut.ac.r N. Yazdan Yazdan@ut.ac.r Control and Intellgent Processng Center

More information

Portfolio Loss Distribution

Portfolio Loss Distribution Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment

More information

Evaluation of the information servicing in a distributed learning environment by using monitoring and stochastic modeling

Evaluation of the information servicing in a distributed learning environment by using monitoring and stochastic modeling MultCraft Internatonal Journal of Engneerng, Scence and Technology Vol, o, 9, -4 ITERATIOAL JOURAL OF EGIEERIG, SCIECE AD TECHOLOGY wwwest-ngcom 9 MultCraft Lmted All rghts reserved Evaluaton of the nformaton

More information

How To Understand The Results Of The German Meris Cloud And Water Vapour Product

How To Understand The Results Of The German Meris Cloud And Water Vapour Product Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller

More information

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS 21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS

More information

Optimal maintenance of a production-inventory system with continuous repair times and idle periods

Optimal maintenance of a production-inventory system with continuous repair times and idle periods Proceedngs o the 3 Internatonal Conerence on Aled Mathematcs and Comutatonal Methods Otmal mantenance o a roducton-nventory system wth contnuous rear tmes and dle erods T. D. Dmtrakos* Deartment o Mathematcs

More information

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Research Note APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES * Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

Dynamic Load Balancing of Parallel Computational Iterative Routines on Platforms with Memory Heterogeneity

Dynamic Load Balancing of Parallel Computational Iterative Routines on Platforms with Memory Heterogeneity Dynamc Load Balancng of Parallel Comutatonal Iteratve Routnes on Platforms wth Memory Heterogenety Davd Clare, Alexey Lastovetsy, Vladmr Rychov School of Comuter Scence and Informatcs, Unversty College

More information

THE APPLICATION OF DATA MINING TECHNIQUES AND MULTIPLE CLASSIFIERS TO MARKETING DECISION

THE APPLICATION OF DATA MINING TECHNIQUES AND MULTIPLE CLASSIFIERS TO MARKETING DECISION Internatonal Journal of Electronc Busness Management, Vol. 3, No. 4, pp. 30-30 (2005) 30 THE APPLICATION OF DATA MINING TECHNIQUES AND MULTIPLE CLASSIFIERS TO MARKETING DECISION Yu-Mn Chang *, Yu-Cheh

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

More information

Bayesian Network Based Causal Relationship Identification and Funding Success Prediction in P2P Lending

Bayesian Network Based Causal Relationship Identification and Funding Success Prediction in P2P Lending Proceedngs of 2012 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 25 (2012) (2012) IACSIT Press, Sngapore Bayesan Network Based Causal Relatonshp Identfcaton and Fundng Success

More information

NEURO-FUZZY INFERENCE SYSTEM FOR E-COMMERCE WEBSITE EVALUATION

NEURO-FUZZY INFERENCE SYSTEM FOR E-COMMERCE WEBSITE EVALUATION NEURO-FUZZY INFERENE SYSTEM FOR E-OMMERE WEBSITE EVALUATION Huan Lu, School of Software, Harbn Unversty of Scence and Technology, Harbn, hna Faculty of Appled Mathematcs and omputer Scence, Belarusan State

More information

DEFINING %COMPLETE IN MICROSOFT PROJECT

DEFINING %COMPLETE IN MICROSOFT PROJECT CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,

More information

Efficient Computation of Optimal, Physically Valid Motion

Efficient Computation of Optimal, Physically Valid Motion Vol. xx No. xx,.1 5, 200x 1 Effcent Comutaton of Otmal, Physcally Vald Moton Anthony C. Fang 1 and Nancy S. Pollard 2 1 Deartment of Comuter Scence, Natonal Unversty of Sngaore 2 Robotcs Insttute, Carnege

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

A Study on Secure Data Storage Strategy in Cloud Computing

A Study on Secure Data Storage Strategy in Cloud Computing Journal of Convergence Informaton Technology Volume 5, Number 7, Setember 00 A Study on Secure Data Storage Strategy n Cloud Comutng Danwe Chen, Yanjun He, Frst Author College of Comuter Technology, Nanjng

More information

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,

More information

The OC Curve of Attribute Acceptance Plans

The OC Curve of Attribute Acceptance Plans The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4

More information

Load Balancing of Parallelized Information Filters

Load Balancing of Parallelized Information Filters IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. XXX, NO. XX, XXXXXXX 2001 1 Load Balancng of Parallelzed Informaton Flters Nel C. Rowe, Member, IEEE Comuter Socety, and Amr Zaky, Member, IEEE

More information

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

More information

Statistical Methods to Develop Rating Models

Statistical Methods to Develop Rating Models Statstcal Methods to Develop Ratng Models [Evelyn Hayden and Danel Porath, Österrechsche Natonalbank and Unversty of Appled Scences at Manz] Source: The Basel II Rsk Parameters Estmaton, Valdaton, and

More information

Different Methods of Long-Term Electric Load Demand Forecasting; A Comprehensive Review

Different Methods of Long-Term Electric Load Demand Forecasting; A Comprehensive Review Dfferent Methods of Long-Term Electrc Load Demand Forecastng; A Comprehensve Revew L. Ghods* and M. Kalantar* Abstract: Long-term demand forecastng presents the frst step n plannng and developng future

More information

Can Auto Liability Insurance Purchases Signal Risk Attitude?

Can Auto Liability Insurance Purchases Signal Risk Attitude? Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang

More information

Machine Learning and Software Quality Prediction: As an Expert System

Machine Learning and Software Quality Prediction: As an Expert System I.J. Informaton Engneerng and Electronc Busness, 2014, 2, 9-27 Publshed Onlne Aprl 2014 n MECS (http://www.mecs-press.org/) DOI: 10.5815/jeeb.2014.02.02 Machne Learnng and Software Qualty Predcton: As

More information

MATHEMATICAL ENGINEERING TECHNICAL REPORTS. Sequential Optimizing Investing Strategy with Neural Networks

MATHEMATICAL ENGINEERING TECHNICAL REPORTS. Sequential Optimizing Investing Strategy with Neural Networks MATHEMATICAL ENGINEERING TECHNICAL REPORTS Sequental Optmzng Investng Strategy wth Neural Networks Ryo ADACHI and Akmch TAKEMURA METR 2010 03 February 2010 DEPARTMENT OF MATHEMATICAL INFORMATICS GRADUATE

More information

Descriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications

Descriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications CMSC828G Prncples of Data Mnng Lecture #9 Today s Readng: HMS, chapter 9 Today s Lecture: Descrptve Modelng Clusterng Algorthms Descrptve Models model presents the man features of the data, a global summary

More information

FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES

FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES Zuzanna BRO EK-MUCHA, Grzegorz ZADORA, 2 Insttute of Forensc Research, Cracow, Poland 2 Faculty of Chemstry, Jagellonan

More information

A Structure Preserving Database Encryption Scheme

A Structure Preserving Database Encryption Scheme A Structure Preservng Database Encryton Scheme Yuval Elovc, Ronen Wasenberg, Erez Shmuel, Ehud Gudes Ben-Guron Unversty of the Negev, Faculty of Engneerng, Deartment of Informaton Systems Engneerng, Postfach

More information

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy 4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information

A COLLABORATIVE TRADING MODEL BY SUPPORT VECTOR REGRESSION AND TS FUZZY RULE FOR DAILY STOCK TURNING POINTS DETECTION

A COLLABORATIVE TRADING MODEL BY SUPPORT VECTOR REGRESSION AND TS FUZZY RULE FOR DAILY STOCK TURNING POINTS DETECTION A COLLABORATIVE TRADING MODEL BY SUPPORT VECTOR REGRESSION AND TS FUZZY RULE FOR DAILY STOCK TURNING POINTS DETECTION JHENG-LONG WU, PEI-CHANN CHANG, KAI-TING CHANG Department of Informaton Management,

More information

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure

More information

Conversion between the vector and raster data structures using Fuzzy Geographical Entities

Conversion between the vector and raster data structures using Fuzzy Geographical Entities Converson between the vector and raster data structures usng Fuzzy Geographcal Enttes Cdála Fonte Department of Mathematcs Faculty of Scences and Technology Unversty of Combra, Apartado 38, 3 454 Combra,

More information

Characterization of Assembly. Variation Analysis Methods. A Thesis. Presented to the. Department of Mechanical Engineering. Brigham Young University

Characterization of Assembly. Variation Analysis Methods. A Thesis. Presented to the. Department of Mechanical Engineering. Brigham Young University Characterzaton of Assembly Varaton Analyss Methods A Thess Presented to the Department of Mechancal Engneerng Brgham Young Unversty In Partal Fulfllment of the Requrements for the Degree Master of Scence

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by 6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng

More information

Research Article Competition and Integration in Closed-Loop Supply Chain Network with Variational Inequality

Research Article Competition and Integration in Closed-Loop Supply Chain Network with Variational Inequality Hndaw Publshng Cororaton Mathematcal Problems n Engneerng Volume 2012, Artcle ID 524809, 21 ages do:10.1155/2012/524809 Research Artcle Cometton and Integraton n Closed-Loo Suly Chan Network wth Varatonal

More information

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho

More information

the Manual on the global data processing and forecasting system (GDPFS) (WMO-No.485; available at http://www.wmo.int/pages/prog/www/manuals.

the Manual on the global data processing and forecasting system (GDPFS) (WMO-No.485; available at http://www.wmo.int/pages/prog/www/manuals. Gudelne on the exchange and use of EPS verfcaton results Update date: 30 November 202. Introducton World Meteorologcal Organzaton (WMO) CBS-XIII (2005) recommended that the general responsbltes for a Lead

More information

Credit Limit Optimization (CLO) for Credit Cards

Credit Limit Optimization (CLO) for Credit Cards Credt Lmt Optmzaton (CLO) for Credt Cards Vay S. Desa CSCC IX, Ednburgh September 8, 2005 Copyrght 2003, SAS Insttute Inc. All rghts reserved. SAS Propretary Agenda Background Tradtonal approaches to credt

More information

INVENTORY MANAGEMENT REVISED

INVENTORY MANAGEMENT REVISED Scence & Mltary 2/2011 INVENTORY MANAGEMENT REVISED Analyss of behavoral asects of decson makng wthn Sales & Oeratons Plannng rocess Peter JUREČKA Abstract: The urose of ths artcle s to extend the standard

More information

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,

More information

Towards an Effective Personalized Information Filter for P2P Based Focused Web Crawling

Towards an Effective Personalized Information Filter for P2P Based Focused Web Crawling Journal of Comuter Scence (1): 97-103, 006 ISS 1549-3636 006 Scence Publcatons Towards an Effectve Personalzed Informaton Flter for PP Based Focused Web Crawlng Fu Xang-hua and Feng Bo-qn Deartment of

More information

Chapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT

Chapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT Chapter 4 ECOOMIC DISATCH AD UIT COMMITMET ITRODUCTIO A power system has several power plants. Each power plant has several generatng unts. At any pont of tme, the total load n the system s met by the

More information

Using Association Rule Mining: Stock Market Events Prediction from Financial News

Using Association Rule Mining: Stock Market Events Prediction from Financial News Usng Assocaton Rule Mnng: Stock Market Events Predcton from Fnancal News Shubhang S. Umbarkar 1, Prof. S. S. Nandgaonkar 2 1 Savtrba Phule Pune Unversty, Vdya Pratshtan s College of Engneerng, Vdya Nagar,

More information

BUSINESS PROCESS PERFORMANCE MANAGEMENT USING BAYESIAN BELIEF NETWORK. 0688, dskim@ssu.ac.kr

BUSINESS PROCESS PERFORMANCE MANAGEMENT USING BAYESIAN BELIEF NETWORK. 0688, dskim@ssu.ac.kr Proceedngs of the 41st Internatonal Conference on Computers & Industral Engneerng BUSINESS PROCESS PERFORMANCE MANAGEMENT USING BAYESIAN BELIEF NETWORK Yeong-bn Mn 1, Yongwoo Shn 2, Km Jeehong 1, Dongsoo

More information

Finite Math Chapter 10: Study Guide and Solution to Problems

Finite Math Chapter 10: Study Guide and Solution to Problems Fnte Math Chapter 10: Study Gude and Soluton to Problems Basc Formulas and Concepts 10.1 Interest Basc Concepts Interest A fee a bank pays you for money you depost nto a savngs account. Prncpal P The amount

More information

Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account

Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account Amercan J. of Engneerng and Appled Scences (): 8-6, 009 ISSN 94-700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a Day-Ahead Electrcty Market wth Rsk Management Taken nto Account

More information

Gender Classification for Real-Time Audience Analysis System

Gender Classification for Real-Time Audience Analysis System Gender Classfcaton for Real-Tme Audence Analyss System Vladmr Khryashchev, Lev Shmaglt, Andrey Shemyakov, Anton Lebedev Yaroslavl State Unversty Yaroslavl, Russa vhr@yandex.ru, shmaglt_lev@yahoo.com, andrey.shemakov@gmal.com,

More information

Statistical Approach for Offline Handwritten Signature Verification

Statistical Approach for Offline Handwritten Signature Verification Journal of Computer Scence 4 (3): 181-185, 2008 ISSN 1549-3636 2008 Scence Publcatons Statstcal Approach for Offlne Handwrtten Sgnature Verfcaton 2 Debnath Bhattacharyya, 1 Samr Kumar Bandyopadhyay, 2

More information

PERFORMANCE ANALYSIS OF PARALLEL ALGORITHMS

PERFORMANCE ANALYSIS OF PARALLEL ALGORITHMS Software Analye PERFORMANCE ANALYSIS OF PARALLEL ALGORIHMS Felcan ALECU PhD, Unverty Lecturer, Economc Informatc Deartment, Academy of Economc Stude, Bucharet, Romana E-mal: alecu.felcan@e.ae.ro Abtract:

More information

Gaining Insights to the Tea Industry of Sri Lanka using Data Mining

Gaining Insights to the Tea Industry of Sri Lanka using Data Mining Proceedngs of the Internatonal MultConference of Engneers and Computer Scentsts 2008 Vol I Ganng Insghts to the Tea Industry of Sr Lanka usng Data Mnng H.C. Fernando, W. M. R Tssera, and R. I. Athauda

More information

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

A Hybrid Model for Forecasting Sales in Turkish Paint Industry Internatonal Journal of Computatonal Intellgence Systems, Vol.2, No. 3 (October, 2009), 277-287 A Hybrd Model for Forecastng Sales n Turksh Pant Industry Alp Ustundag * Department of Industral Engneerng,

More information

Chapter 3: Dual-bandwidth Data Path and BOCP Design

Chapter 3: Dual-bandwidth Data Path and BOCP Design Chater 3: Dual-bandwdth Data Path and BOCP Desgn 3. Introducton The focus of ths thess s on the 4G wreless moble Internet networks to rovde data servces wthn the overlang areas of CDA2000-WLA networks.

More information

A Secure Password-Authenticated Key Agreement Using Smart Cards

A Secure Password-Authenticated Key Agreement Using Smart Cards A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,

More information

Determination of Integrated Risk Degrees in Product Development Project

Determination of Integrated Risk Degrees in Product Development Project Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA Determnaton of Integrated sk Degrees n Product Development Project D. W. Cho.,

More information

v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

v a 1 b 1 i, a 2 b 2 i,..., a n b n i. SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 455 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces we have studed thus far n the text are real vector spaces snce the scalars are

More information

Modeling and Prediction of Pedestrian Behavior based on the Sub-goal Concept

Modeling and Prediction of Pedestrian Behavior based on the Sub-goal Concept Modelng and Predcton of Pedestran Behavor based on the Sub-goal Concet Tetsush Ieda, Yoshhro Chgodo, Danel Rea, Francesco Zanlungo, Masahro Shom, Taayu Kanda Intellgent Robotcs and Communcaton Laboratores,

More information

Decision Tree Model for Count Data

Decision Tree Model for Count Data Proceedngs of the World Congress on Engneerng 2012 Vol I Decson Tree Model for Count Data Yap Bee Wah, Norashkn Nasaruddn, Wong Shaw Voon and Mohamad Alas Lazm Abstract The Posson Regresson and Negatve

More information

Estimating the Development Effort of Web Projects in Chile

Estimating the Development Effort of Web Projects in Chile Estmatng the Development Effort of Web Projects n Chle Sergo F. Ochoa Computer Scences Department Unversty of Chle (56 2) 678-4364 sochoa@dcc.uchle.cl M. Cecla Bastarrca Computer Scences Department Unversty

More information

Offline Verification of Hand Written Signature using Adaptive Resonance Theory Net (Type-1)

Offline Verification of Hand Written Signature using Adaptive Resonance Theory Net (Type-1) Internatonal Journal of Sgnal Processng Systems Vol, No June 203 Offlne Verfcaton of Hand Wrtten Sgnature usng Adaptve Resonance Theory Net (Type-) Trtharaj Dash Veer Surendra Sa Unversty of Technology,

More information

Recent Advances in Business Management and Marketing

Recent Advances in Business Management and Marketing Recent Advances n Busness anagement and aretng A Sales Growth odel for Small Enterrses ARTIN ACHE, ONDŘEJ ACHE Deartment of aretng, Deartment of Busness Economcs Unversty of Economcs, Prague W. Churchll

More information

Semantic Link Analysis for Finding Answer Experts *

Semantic Link Analysis for Finding Answer Experts * JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 28, 51-65 (2012) Semantc Lnk Analyss for Fndng Answer Experts * YAO LU 1,2,3, XIAOJUN QUAN 2, JINGSHENG LEI 4, XINGLIANG NI 1,2,3, WENYIN LIU 2,3 AND YINLONG

More information

Design and Development of a Security Evaluation Platform Based on International Standards

Design and Development of a Security Evaluation Platform Based on International Standards Internatonal Journal of Informatcs Socety, VOL.5, NO.2 (203) 7-80 7 Desgn and Development of a Securty Evaluaton Platform Based on Internatonal Standards Yuj Takahash and Yoshm Teshgawara Graduate School

More information

Study on Model of Risks Assessment of Standard Operation in Rural Power Network

Study on Model of Risks Assessment of Standard Operation in Rural Power Network Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,

More information

Business Process Improvement using Multi-objective Optimisation K. Vergidis 1, A. Tiwari 1 and B. Majeed 2

Business Process Improvement using Multi-objective Optimisation K. Vergidis 1, A. Tiwari 1 and B. Majeed 2 Busness Process Improvement usng Mult-objectve Optmsaton K. Vergds 1, A. Twar 1 and B. Majeed 2 1 Manufacturng Department, School of Industral and Manufacturng Scence, Cranfeld Unversty, Cranfeld, MK43

More information

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION

More information

Prediction Model for Characteristics of Implementation of Information Systems in Small and Medium Enterprises

Prediction Model for Characteristics of Implementation of Information Systems in Small and Medium Enterprises Predcton Model for Characterstcs of Implementaton of Informaton Systems n Small and Medum Enterprses I. Nazor, K. Fertalj, and D. Kalpc Abstract The process of choosng an Enterprse Resource Plannng (ERP)

More information

Presented at the World Conference on Transportation Research, 2007

Presented at the World Conference on Transportation Research, 2007 ESTIMATES OF AADT: QUANTIFYING THE UNCERTAINTY Shashank Chowdary Gadda Credt Polcy/Rsk Analyst HSBC 1441 Schllng Place Salnas, CA.93902 Emal: shashankgc@gmal.com Kara M. Kockelman Assocate Professor and

More information

An Analytical Model for Multi-tier Internet Services and Its Applications

An Analytical Model for Multi-tier Internet Services and Its Applications An Analytcal Model for Mult-ter Internet Servces and Its Alcatons Bhuvan Urgaonkar, Govann Pacfc, Prashant Shenoy, Mke Sretzer, and Asser Tantaw Det. of Comuter Scence, Servce Management Mddleware Det.,

More information

Construction Rules for Morningstar Canada Target Dividend Index SM

Construction Rules for Morningstar Canada Target Dividend Index SM Constructon Rules for Mornngstar Canada Target Dvdend Index SM Mornngstar Methodology Paper October 2014 Verson 1.2 2014 Mornngstar, Inc. All rghts reserved. The nformaton n ths document s the property

More information

J. Parallel Distrib. Comput.

J. Parallel Distrib. Comput. J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n

More information

JCM_VN_AM003_ver01.0 Sectoral scope: 03

JCM_VN_AM003_ver01.0 Sectoral scope: 03 Sectoral scoe: 03 Jont Credtng Mechansm Aroved Methodology VN_AM003 Imrovng the energy effcency of commercal buldngs by utlzaton of hgh effcency equment A. Ttle of the methodology Imrovng the energy effcency

More information

Number of Levels Cumulative Annual operating Income per year construction costs costs ($) ($) ($) 1 600,000 35,000 100,000 2 2,200,000 60,000 350,000

Number of Levels Cumulative Annual operating Income per year construction costs costs ($) ($) ($) 1 600,000 35,000 100,000 2 2,200,000 60,000 350,000 Problem Set 5 Solutons 1 MIT s consderng buldng a new car park near Kendall Square. o unversty funds are avalable (overhead rates are under pressure and the new faclty would have to pay for tself from

More information

A neuro-fuzzy collaborative filtering approach for Web recommendation. G. Castellano, A. M. Fanelli, and M. A. Torsello *

A neuro-fuzzy collaborative filtering approach for Web recommendation. G. Castellano, A. M. Fanelli, and M. A. Torsello * Internatonal Journal of Computatonal Scence 992-6669 (Prnt) 992-6677 (Onlne) Global Informaton Publsher 27, Vol., No., 27-39 A neuro-fuzzy collaboratve flterng approach for Web recommendaton G. Castellano,

More information

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM BARRIOT Jean-Perre, SARRAILH Mchel BGI/CNES 18.av.E.Beln 31401 TOULOUSE Cedex 4 (France) Emal: jean-perre.barrot@cnes.fr 1/Introducton The

More information

320 The Internatonal Arab Journal of Informaton Technology, Vol. 5, No. 3, July 2008 Comparsons Between Data Clusterng Algorthms Osama Abu Abbas Computer Scence Department, Yarmouk Unversty, Jordan Abstract:

More information

Context-aware Mobile Recommendation System Based on Context History

Context-aware Mobile Recommendation System Based on Context History TELKOMNIKA Indonesan Journal of Electrcal Engneerng Vol.12, No.4, Aprl 2014, pp. 3158 ~ 3167 DOI: http://dx.do.org/10.11591/telkomnka.v124.4786 3158 Context-aware Moble Recommendaton System Based on Context

More information

Cloud-based Social Application Deployment using Local Processing and Global Distribution

Cloud-based Social Application Deployment using Local Processing and Global Distribution Cloud-based Socal Applcaton Deployment usng Local Processng and Global Dstrbuton Zh Wang *, Baochun L, Lfeng Sun *, and Shqang Yang * * Bejng Key Laboratory of Networked Multmeda Department of Computer

More information

Mining Multiple Large Data Sources

Mining Multiple Large Data Sources The Internatonal Arab Journal of Informaton Technology, Vol. 7, No. 3, July 2 24 Mnng Multple Large Data Sources Anmesh Adhkar, Pralhad Ramachandrarao 2, Bhanu Prasad 3, and Jhml Adhkar 4 Department of

More information