Journal of Engineering and Natural Sciences Mühendislik ve Fen Bilimleri Dergisi


 Beverley Carroll
 2 years ago
 Views:
Transcription
1 Journal of Engneerng and Natural Scences Mühendslk ve Fen Blmler Dergs Sgma 005/1 A NEW APPROACH BASED ON HOPFIELD NEURAL NETWORK TO ECONOMIC LOAD DISPATCH Naser Mahdav TABATABAEI 1, Ahmet NAYIR *, Gholam AHMADI 3 1 Electrcal Engneerng Department, Azarbaan Unversty of Tarbat Moallem, TabrzIRAN Insttute of Energy, Istanbul Techncal Unversty, Ayazağa Kampüsü,MaslakISTANBUL 3 Electrcal Engneerng Department, Unversty of Tabrz, TabrzIRAN Gelş/Receved: Kabul/Accepted: ABSTRACT The Economc Load Dspatch (ELD) problem s how to real power output of each controlled generatng unt n an area s selected to meet a gven load and to mnmze the total operatng cost n the area. Ths s one of the mportant problems n a power system. The Hopfeld Neural Network (HNN) has a good capablty to solve optmzaton problems. Recently, the economc load dspatch problem solved by usng the Hopfeld neural network approach and good result has obtaned. Ths paper presents a new approach for solvng ELD problem consderng the returnng cost usng HNN model. In ths approach two energy functons are ntroduced. The frst energy functon consst of msmatch power, total fuel cost and transmsson lne losses. Each term of ths functon s multpled by a weghtng factor whch represents the relatve mportance of those terms. The other energy functon composed of total fuel cost and losses power cost. Our purpose s to mnmze these two functon and the results shows that solvng ELD problem wth ths approach yeld more savng cost. Keywords: HNN, ELD, Power system, Lagrangan method, Transmsson lne losses. EKONOMİK YÜK RAPORUNDA HOPFIELD SİNİR AĞINA DAYALI YENİ BİR YAKLAŞIM ÖZET Ekonomk yük raporu (ELD) problem bu alandak toplam en düşük şletm malyet ve verlen br yük le karşıldığında br alanda kontrol edlen her br üretm brmnn gerçek güç çıkışıdır. Bu güç sstemndek öneml br problemdr. Hopfeld snr ağı (HNN) en y kullanım problemlernn çözümünde y br kapasteye sahptr. Son zamanlardak ekonomk yük raporu problem Hopfeld snr ağı yaklaşımı kullanılarak çözülmüş ve y sonuç elde edlmştr. Bu makale, HNN model kullanılarak gerletlen malyet göz önüne alınarak ELD problemnn çözümünde yen br yaklaşımı arz etmektedr. Bu yaklaşımda k ener fonsyonu arz edlmektedr. İlk ener fonksyonu, toplam yakıt malyet ve taşıma hattı kayıbı olan, msmatch gücünden barettr. Bu fonksyonun her br term bu termlern brbrne göre önemn arz eden br faktörle çarpılır. Ötek ener fonksyonu toplam yakıt malyetnden ve güç malyet kayıbından barettr. Amacımız bu k fonksyonu mnmze etmektr ve sonuçlar malyetn daha çok korunduğu bu yaklaşım vermyle ELD problemnn çözüldüğünü göstermştr. Anahtar Sözcükler: HNN, ELD, Güç sstem, Lagrangan metodu, İletm hattı kaybı. * Sorumlu Yazar/Correspondng Author; eposta: tel: (01)
2 N. M. Tabatabae, A. Nayır, G. Ahmad Sgma 005/1 1. INTRODUCTION Economc load dspatch s one of the most mportant problems n a power system. The goal of solvng ths problem s obtanng optmum generatng power for generaton unts n an electrc power system to meet a gven load and to mnmze the total operatng cost. For solvng ths problem, many approaches have presented. One of them s Lagrangan method. In ths method a Lagrangan augmented functon s frst formulated [13]. The optmal condtons are obtaned by partal dervaton of ths functon. Calculaton of the penalty factors and ncremental losses s always the key ponts n the soluton algorthm. Incremental losses and thus the penalty factors are determned by the Bcoeffcent method whch states that the transmsson losses can be expressed n quadratc forms of the generaton powers. Recently, the ELD problem has been solved by usng the Hopfeld Neural Network and genetc algorthm. The HNN has a good capablty to solve optmzaton problems. In ths method the obectve functon of ELD problem s transformed n to a Hopfeld energy functon and numercal teraton are appled to mnmze the energy functon. Gee and Prager ntroduced methods to mprove the HNN approach by ntroducng slack varables for handlng nequalty constrants [4]. J.H. Park et. al have proposed a method to use the HNN to solve the ELD problem wth a pecewse quadratc cost functons [5]. HNN converges very slowly whch n the advantage methods have been used to update the slops or bas of the network to speed the convergence. The pecewse quadratc cost functons n ELD are used to represent multple fuels whch are avalable to each generaton unt. In these unts t may be more economcal to burn a certan fuel for some MW outputs and another knd of fuel for other outputs [6]. Reducng of transmsson lne losses s another parameter whch must be taken nto account n ths problem, because transmsson losses are the energes that the customers don t pay drectly ther costs. In ths paper a new approach and mappng technque s presented for solvng ELD problem n a power system, consderng the cost that customer pay t, by usng HNN. The proposed method has also acheved effcent and accurate solutons for dfferent szes of power systems.. ECONOMIC LOAD DISPATCH MODEL The ELD problem s to fnd the optmal soluton of power generaton that mnmzes the total cost whle satsfyng the system constrants. Mathematcally, ths problem can be expressed as [1]: C = ( a + b P + cp ) (1) P : The power output of th generator a, : Cost coeffcents of th generator b, c C : The generaton cost of the th plant Subect to satsfyng the followng constrants: (a) The actve power balance equaton: P = PL + PD () P = PB P (3) L P D : Total demand load 46
3 A New Approach Based on Hopfeld Neural P L : Transmsson loss B : Transmsson loss coeffcents (b) Maxmum and mnmum lmt of power: P = P = P (4), mn, max P : The mnmum generaton lmt of unt, mn P, max : The maxmum generaton lmt of unt The well known soluton method to ths problem usng the coordnaton equaton s df( P) PF df ( P ) df( P) 1 1 k k 1 =... = PFk =... = PF (5) df1 dpk dp PF k k PF k s the penalty factor of unt k gven by 1 = 1 P / P = 1,,..., L k, and PL / Pk s the ncremental loss of unt k. The penalty factors can be computed from losses formula (3). 3. THE STANDARD HOPFIELD NEURAL NETWORK The Hopfeld neural network conssts of a set of neurons and a correspondng set of unt delays, formng a multple loop feedback system. The number of feedback loops s equal to the number of neurons. The nput of neuron s suppled by two dfferent sources, e.g., the output of other neurons and the external nput. The nputoutput relaton s descrbed generally by a sgmod functon gven below []: V = g ( U) (7) V s a contnuous varable n the nterval 0 to 1, and g ( U ) s a ncreasng functon whch constrants V to ths nterval. 1 g( U) = (8) U 1+ exp( ) u 0 U : The total nput of neuron V : The output of neuron u 0 : The shape constant of sgmod functon The dynamc characterstc equaton of the system can be descrbed by: du dt = T V + I I : The nput bas current to neuron (6) (9) 47
4 N. M. Tabatabae, A. Nayır, G. Ahmad Sgma 005/1 T : Interconnecton conductance from the output of neuron to the nput of neuron T : Self connecton conductance of neuron The energy functon of the Hopfeld neural network s defned as [4]: E = ( 1/ ) T V V I V (1 The tme dervatve of the energy functon can be proven to be negatve: de / dt < 0 (11) So the model state always moves n such a way that the energy functon gradually reduces and converges to a mnmum. 4. TRANSFORM OBJECTIVE FUNCTION INTO HOPFIELD ENERGY FUNCTION To solve the ELD problem usng the Hopfeld method wth consderng returnng cost, two energy functons are defned as follows [3]: E1 = ( A/ )[( PD ) P ] + ( B / ) ( a + b P + cp ) + ( C / ) P (1) and E ( a + b P + cp ) + 90PL = (13) The frst energy functon, E 1, s composed of power msmatch, total fuel cost and transmsson lne losses. The postve weghtng factors A, B and C ntroduce the relatve mportance for ther respectve assocated terms and they are determned by tral and error. The other energy functon, E, s consst of total generatng cost and transmsson losses cost whch the cost doesn t return to the system and our goal s to reduce that [5, 6]. Consderng $0.09 for each KWh energy ($90 for each MWh), the cost of transmsson losses wll be 90 PL whch taken nto account n E. If the generaton output of unt changes from P 0 to P then the transmsson losses wll change from P L0 to P L, whch may be expressed as P L PL 0 + IL0( P P (14) I L0 s the ncremental loss of unt at power generaton of P 0. Substtutng (1 nto (9) yelds E1 = ( A/ )[( PD ) P ] + ( B / ) ( a + b P + cp ) + ( C / )( PL 0 + I L0 ( P P 0 )) so E1 ( A/ )( PD + ( B / ) a + ( C / )( PL 0 I L0P [ A( PD 0 ) ( Bb / ) ( C / ) I L0] P + ( A + Bc ) P / + AP P / then E 1 H [ A( PD ( Bb / ) ( C / ) I L0] P + ( A + Bc ) P / + ( AP P / ) (15) Where H s a constant and s equal 48
5 A New Approach Based on Hopfeld Neural a + ( C / )( PL 0 H = ( A/ )( PD 0 ) + ( B/ ) IL0P (16) and E = a + b P + c P ) + 90 PB P = G + ( b ) P + ( c + 90B) P + 90 BP P 1 ( (17) Where G s a constant and G = a (18) The power output value, P, n Hopfeld model can be expressed as follows: P = g( U) = ( P, max P, mn)/(1 + exp( U / u) + P, mn (19) By comparng (1 wth (1) the weght parameters and external nput of neuron n the network are gven T = A Bc T = A ( I = A( PD Bb / CIL0 / By usng (9) and ( we have U = { A( PD 0 P ) ( B / )( b + c P ) CI L 0 / } t, (1) P = g ( U ) For computng energy functon, E, by comparng (1 and (13) the followng equaton are gven T = ( c + 90B ) / T = 90B () I = b / By usng equatons (9) and () we have U = {(( 90B )/ ) V ) ( c / ) V b / )} t, P = g ( U ) Usng teraton methods, equatons (1) and (3) can be solved separately. In each teraton, the output of each neuron must be updated untl the soluton converges gradually to ther feasble local mnmum. 5. SIMULATION RESULTS To llustrate the applcaton of the proposed method, an example system s employed. The example system has 0 generatng unts to supply a total load demand of 0 MW [3, 6]. Table 1 gves fuel cost coeffcent and generaton lmts for each unt. Weghtng factors A, B and C are obtaned from tral and error. The computaton results whch are obtaned by usng teraton method and proposed approach are gven n Table. Accordng to Table we fnd that the generatng value for each unt, whch are obtaned from proposed method, has a lttle dfference wth ts value, whch are obtaned from teraton method, whle transmsson losses s smaller n the proposed method. (3) 49
6 N. M. Tabatabae, A. Nayır, G. Ahmad Sgma 005/1 Fgure 1 shows the lttle dfference between two methods. The cost that consume for generatng power and transmsson losses, related to two methods s calculated as follows: C 1 = = $/h and C = = $/h C 1 s the cost n λ method and C s ths cost n the proposed method. From the values of C 1 and C t s obvous that the consumed cost n the proposed method s small and the dfference s equal C 1 C = $/h = $/year In the other words, f we use the proposed method that s presented n ths paper, more cost wll be saved n one year. 6. CONCLUSIONS Ths paper presents a new method based on Hopfeld model for solvng economc load dspatch problem. The proposed method essentally obeys the equalncrementalcost crteron followed by conventonal economc dspatch methods. The Hopfeld neural network has a nonherarchcal structure and ts connectve conductances and external nput can be determned by employng the system data. Thus, the proposed model unlke other neural networks requres no tranng. Usng the Hopfeld neural network for solvng economc load dspatch decreases computaton tme. Table 1. The coeffcent of total fuel cost functon and generatng power lmt unts of test system Unt a ($/h) b ($/MWh) c ($/MWh) P, mn (MW) P, max MW)
7 A New Approach Based on Hopfeld Neural Table. Computaton results of two methods n the test system Unt Generaton (MW) P 1 P P 3 P 4 P 5 P 6 P 7 P 8 P 9 P 10 P 11 P 1 P 13 P 14 P 15 P 16 P 17 P 18 P 19 P 0 P LOSS λ Iteraton Method The Proposed Method Fgure 1. The λ teraton method values and the proposed method values for the test system 51
8 N. M. Tabatabae, A. Nayır, G. Ahmad Sgma 005/1 REFERENCES [1] Happ H.H., "Optmal Power Dspatch," IEEE Transactons PAS, vol. PAS93, pp , [] Ln C.E., Chen S.T. and Huang C.L., "A Drect NewtonRophson Economc Dspatch," IEEE Transactons on Power System, vol. 7, no. 3, pp , 199. [3] Su C.T. and Chou G.J., "A Fast Computaton Hopfeld Method to Economc Dspatch of Power System," IEEE Transactons on Power Systems, vol. 1, no. 4, pp , [4] Gee A.H. and Prager R.W., "Polyhedral Combnatorcs and Neural Networks," Neural Computng, vol. 6, pp , [5] Park J.H., Km Y.S., Eom I. K. and Lee K. Y., "Economc Load Dspatch for Pecewse Quadratc Cost Functon Usng Hopfeld Neural Network," IEEE Transactons on Power System, vol. 8, no. 3, pp , [6] Lee K.Y., SodeYome A. and Park J.H., "Adaptve Hopfeld Neural Networks for Economc Load Dspatch", IEEE Tansactons on Power Systems, vol. 13, no., pp , May
Dynamic Constrained Economic/Emission Dispatch Scheduling Using Neural Network
Dynamc Constraned Economc/Emsson Dspatch Schedulng Usng Neural Network Fard BENHAMIDA 1, Rachd BELHACHEM 1 1 Department of Electrcal Engneerng, IRECOM Laboratory, Unversty of Djllal Labes, 220 00, Sd Bel
More informationChapter 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 informationA 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):18841889 Research Artcle ISSN : 09757384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationA Computer Technique for Solving LP Problems with Bounded Variables
Dhaka Unv. J. Sc. 60(2): 163168, 2012 (July) A Computer Technque for Solvng LP Problems wth Bounded Varables S. M. Atqur Rahman Chowdhury * and Sanwar Uddn Ahmad Department of Mathematcs; Unversty of
More informationSupport Vector Machines
Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.
More informationForecasting 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"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, 789794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationThe Development of Web Log Mining Based on ImproveKMeans Clustering Analysis
The Development of Web Log Mnng Based on ImproveKMeans Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationOptimal Bidding Strategies for Generation Companies in a DayAhead Electricity Market with Risk Management Taken into Account
Amercan J. of Engneerng and Appled Scences (): 86, 009 ISSN 94700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a DayAhead Electrcty Market wth Rsk Management Taken nto Account
More informationLogistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification
Lecture 4: More classfers and classes C4B Machne Learnng Hlary 20 A. Zsserman Logstc regresson Loss functons revsted Adaboost Loss functons revsted Optmzaton Multple class classfcaton Logstc Regresson
More informationModule 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 informationInstitute 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 informationProject Networks With MixedTime Constraints
Project Networs Wth MxedTme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationResearch Article Enhanced TwoStep Method via Relaxed Order of αsatisfactory Degrees for Fuzzy Multiobjective Optimization
Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced TwoStep Method va Relaxed Order of αsatsfactory Degrees for Fuzzy
More informationHeuristic Static LoadBalancing Algorithm Applied to CESM
Heurstc Statc LoadBalancng Algorthm Appled to CESM 1 Yur Alexeev, 1 Sher Mckelson, 1 Sven Leyffer, 1 Robert Jacob, 2 Anthony Crag 1 Argonne Natonal Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439,
More informationEducational Software for Economic Load Dispatch for Power Network of Thermal Units Considering Transmission Losses and Spinning Reserve Power
Educatonal Software for Economc Load Dspatch for ower Network of Thermal Unts Consderng Transmsson Losses and Spnnng Reserve ower Mohammad T. Amel Saed Moslehpour Massoud ourhassan ower and Water Unversty
More informationAnt Colony Optimization for Economic Generator Scheduling and Load Dispatch
Proceedngs of the th WSEAS Int. Conf. on EVOLUTIONARY COMPUTING, Lsbon, Portugal, June 118, 5 (pp17175) Ant Colony Optmzaton for Economc Generator Schedulng and Load Dspatch K. S. Swarup Abstract Feasblty
More informationPeriod and Deadline Selection for Schedulability in RealTime Systems
Perod and Deadlne Selecton for Schedulablty n RealTme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng
More informationThe Application of Fractional Brownian Motion in Option Pricing
Vol. 0, No. (05), pp. 738 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qngxn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com
More informationOn the Optimal Control of a Cascade of HydroElectric Power Stations
On the Optmal Control of a Cascade of HydroElectrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More informationA GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION
A GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION Helena Vasconcelos INESC Porto hvasconcelos@nescportopt J N Fdalgo INESC Porto and FEUP jfdalgo@nescportopt
More informationAn MILP model for planning of batch plants operating in a campaignmode
An MILP model for plannng of batch plants operatng n a campagnmode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafeconcet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño
More informationRESEARCH ON DUALSHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.
ICSV4 Carns Australa 9 July, 007 RESEARCH ON DUALSHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract
More informationBERNSTEIN POLYNOMIALS
OnLne 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 informationMaintenance Scheduling by using the BiCriterion Algorithm of Preferential AntiPheromone
Leonardo ournal of Scences ISSN 5830233 Issue 2, anuaryune 2008 p. 4364 Mantenance Schedulng by usng the BCrteron Algorthm of Preferental AntPheromone Trantafyllos MYTAKIDIS and Arstds VLACHOS Department
More informationNonlinear data mapping by neural networks
Nonlnear data mappng by neural networks R.P.W. Dun Delft Unversty of Technology, Netherlands Abstract A revew s gven of the use of neural networks for nonlnear mappng of hgh dmensonal data on lower dmensonal
More informationPAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of IllinoisUrbana Champaign
PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of IllnosUrbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng
More informationCommunication Networks II Contents
8 / 1  Communcaton Networs II (Görg)  www.comnets.unbremen.de Communcaton Networs II Contents 1 Fundamentals of probablty theory 2 Traffc n communcaton networs 3 Stochastc & Marovan Processes (SP
More informationImproved SVM in Cloud Computing Information Mining
Internatonal Journal of Grd Dstrbuton Computng Vol.8, No.1 (015), pp.3340 http://dx.do.org/10.1457/jgdc.015.8.1.04 Improved n Cloud Computng Informaton Mnng Lvshuhong (ZhengDe polytechnc college JangSu
More informationLoop Parallelization
  Loop Parallelzaton C52 Complaton steps: nested loops operatng on arrays, sequentell executon of teraton space DECLARE B[..,..+] FOR I :=.. FOR J :=.. I B[I,J] := B[I,J]+B[I,J] ED FOR ED FOR analyze
More informationFuzzy Set Approach To Asymmetrical Load Balancing In Distribution Networks
Fuzzy Set Approach To Asymmetrcal Load Balancng n Dstrbuton Networks Goran Majstrovc Energy nsttute Hrvoje Por Zagreb, Croata goran.majstrovc@ehp.hr Slavko Krajcar Faculty of electrcal engneerng and computng
More informationChapter 7. RandomVariate Generation 7.1. Prof. Dr. Mesut Güneş Ch. 7 RandomVariate Generation
Chapter 7 RandomVarate Generaton 7. Contents Inversetransform Technque AcceptanceRejecton Technque Specal Propertes 7. Purpose & Overvew Develop understandng of generatng samples from a specfed dstrbuton
More informationA New Task Scheduling Algorithm Based on Improved Genetic Algorithm
A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng
More informationFeature 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 informationEfficient Project Portfolio as a tool for Enterprise Risk Management
Effcent Proect Portfolo as a tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company January 5, 27 Effcent Proect Portfolo as a tool for Enterprse
More informationForecasting 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 informationMooring Pattern Optimization using Genetic Algorithms
6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May  03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz
More informationAn efficient constraint handling methodology for multiobjective evolutionary algorithms
Rev. Fac. Ing. Unv. Antoqua N. 49. pp. 141150. Septembre, 009 An effcent constrant handlng methodology for multobjectve evolutonary algorthms Una metodología efcente para manejo de restrccones en algortmos
More informationAn 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 informationAnalysis of Reactivity Induced Accident for Control Rods Ejection with Loss of Cooling
Analyss of Reactvty Induced Accdent for Control Rods Ejecton wth Loss of Coolng Hend Mohammed El Sayed Saad 1, Hesham Mohammed Mohammed Mansour 2 Wahab 1 1. Nuclear and Radologcal Regulatory Authorty,
More informationAPPLICATION OF COMPUTER PROGRAMMING IN OPTIMIZATION OF TECHNOLOGICAL OBJECTIVES OF COLD ROLLING
Journal Journal of Chemcal of Chemcal Technology and and Metallurgy, 50, 6, 50, 2015, 6, 2015 638643 APPLICATION OF COMPUTER PROGRAMMING IN OPTIMIZATION OF TECHNOLOGICAL OBJECTIVES OF COLD ROLLING Abdrakhman
More information8.5 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 informationAnts Can Schedule Software Projects
Ants Can Schedule Software Proects Broderck Crawford 1,2, Rcardo Soto 1,3, Frankln Johnson 4, and Erc Monfroy 5 1 Pontfca Unversdad Católca de Valparaíso, Chle FrstName.Name@ucv.cl 2 Unversdad Fns Terrae,
More informationDynamic Pricing for Smart Grid with Reinforcement Learning
Dynamc Prcng for Smart Grd wth Renforcement Learnng ByungGook Km, Yu Zhang, Mhaela van der Schaar, and JangWon Lee Samsung Electroncs, Suwon, Korea Department of Electrcal Engneerng, UCLA, Los Angeles,
More informationPrice Competition in an Oligopoly Market with Multiple IaaS Cloud Providers
Prce Competton n an Olgopoly Market wth Multple IaaS Cloud Provders Yuan Feng, Baochun L, Bo L Department of Computng, Hong Kong Polytechnc Unversty Department of Electrcal and Computer Engneerng, Unversty
More informationTHE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek
HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo
More informationA SURVEY ON REACTIVE POWER OPTIMIZATION AND VOLTAGE STABILITY IN POWER SYSTEMS
Internatonal Journal on Techncal and Physcal Problems of Engneerng (IJTPE) Publshed by Internatonal Organzaton of IOTPE ISSN 077358 IJTPE Journal www.otpe.com jtpe@otpe.com March 014 Issue 18 Volume 6
More informationCausal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting
Causal, Explanatory Forecastng Assumes causeandeffect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of
More informationA Binary Particle Swarm Optimization Algorithm for Lot Sizing Problem
Journal o Economc and Socal Research 5 (2), 2 A Bnary Partcle Swarm Optmzaton Algorthm or Lot Szng Problem M. Fath Taşgetren & YunCha Lang Abstract. Ths paper presents a bnary partcle swarm optmzaton
More informationOpen Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 2014, 8, 115121 115 Open Access A Load Balancng Strategy wth Bandwdth Constrant n Cloud Computng Jng Deng 1,*,
More informationECONOMIC load dispatch (ELD) is a nonlinear constrained
1 Stochastc RealTme Schedulng of Wndthermal Generaton Unts n an Electrc Utlty Alreza Soroud, Member, IEEE, Abbas Rabee, Member, IEEE, and Andrew Keane, Senor Member, IEEE Abstract The objectve of dynamc
More informationRELIABILITY, RISK AND AVAILABILITY ANLYSIS OF A CONTAINER GANTRY CRANE ABSTRACT
Kolowrock Krzysztof Joanna oszynska MODELLING ENVIRONMENT AND INFRATRUCTURE INFLUENCE ON RELIABILITY AND OPERATION RT&A # () (Vol.) March RELIABILITY RIK AND AVAILABILITY ANLYI OF A CONTAINER GANTRY CRANE
More informationLecture 2: Single Layer Perceptrons Kevin Swingler
Lecture 2: Sngle Layer Perceptrons Kevn Sngler kms@cs.str.ac.uk Recap: McCullochPtts Neuron Ths vastly smplfed model of real neurons s also knon as a Threshold Logc Unt: W 2 A Y 3 n W n. A set of synapses
More informationA DATA MINING APPLICATION IN A STUDENT DATABASE
JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES JULY 005 VOLUME NUMBER (5357) A DATA MINING APPLICATION IN A STUDENT DATABASE Şenol Zafer ERDOĞAN Maltepe Ünversty Faculty of Engneerng BüyükbakkalköyIstanbul
More informationFORCED CONVECTION HEAT TRANSFER IN A DOUBLE PIPE HEAT EXCHANGER
FORCED CONVECION HEA RANSFER IN A DOUBLE PIPE HEA EXCHANGER Dr. J. Mchael Doster Department of Nuclear Engneerng Box 7909 North Carolna State Unversty Ralegh, NC 276957909 Introducton he convectve heat
More informationRecurrence. 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行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告
行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告 畫 類 別 : 個 別 型 計 畫 半 導 體 產 業 大 型 廠 房 之 設 施 規 劃 計 畫 編 號 :NSC 962628E009026MY3 執 行 期 間 : 2007 年 8 月 1 日 至 2010 年 7 月 31 日 計 畫 主 持 人 : 巫 木 誠 共 同
More informationSolutions to First Midterm
rofessor Chrstano Economcs 3, Wnter 2004 Solutons to Frst Mdterm. Multple Choce. 2. (a) v. (b). (c) v. (d) v. (e). (f). (g) v. (a) The goods market s n equlbrum when total demand equals total producton,.e.
More informationJ. 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 informationMethod for Production Planning and Inventory Control in Oil
Memors of the Faculty of Engneerng, Okayama Unversty, Vol.41, pp.2030, January, 2007 Method for Producton Plannng and Inventory Control n Ol Refnery TakujImamura,MasamKonshandJunIma Dvson of Electronc
More informationIDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS
IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS Chrs Deeley* Last revsed: September 22, 200 * Chrs Deeley s a Senor Lecturer n the School of Accountng, Charles Sturt Unversty,
More informationTesting and Debugging Resource Allocation for Fault Detection and Removal Process
Internatonal Journal of New Computer Archtectures and ther Applcatons (IJNCAA) 4(4): 9300 The Socety of Dgtal Informaton and Wreless Communcatons, 04 (ISSN: 09085) Testng and Debuggng Resource Allocaton
More informationA DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATIONBASED OPTIMIZATION. Michael E. Kuhl Radhamés A. TolentinoPeña
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 SIMULATIONBASED OPTIMIZATION
More informationThe 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 informationPricing Energy and Ancillary Services in Integrated Market Systems by an Optimal Power Flow
Prcng Energy and Ancllary Servces n Integrated Maret Systems by an Optmal Power Flow Tong Wu, Member, IEEE, Mar Rothleder, Member, IEEE, Zad Alaywan, Senor Member, IEEE, Alex D. Papalexopoulos, Fellow,
More informationResource Scheduling in Desktop Grid by GridJQA
The 3rd Internatonal Conference on Grd and Pervasve Computng  Worshops esource Schedulng n Destop Grd by GrdJQA L. Mohammad Khanl M. Analou Assstant professor Assstant professor C.S. Dept.Tabrz Unversty
More informationA GENETIC ALGORITHMBASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES
82 Internatonal Journal of Electronc Busness Management, Vol. 0, No. 3, pp. 8293 (202) A GENETIC ALGORITHMBASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES FengCheng Yang * and WeTng Wu
More informationWhat 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 informationAnswer: 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 MultpleChoce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multplechoce questons. For each queston, only one of the answers s correct.
More informationPowerofTwo Policies for Single Warehouse MultiRetailer Inventory Systems with Order Frequency Discounts
Powerofwo Polces for Sngle Warehouse MultRetaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
More information1 Approximation Algorithms
CME 305: Dscrete Mathematcs and Algorthms 1 Approxmaton Algorthms In lght of the apparent ntractablty of the problems we beleve not to le n P, t makes sense to pursue deas other than complete solutons
More informationGraph Theory and Cayley s Formula
Graph Theory and Cayley s Formula Chad Casarotto August 10, 2006 Contents 1 Introducton 1 2 Bascs and Defntons 1 Cayley s Formula 4 4 Prüfer Encodng A Forest of Trees 7 1 Introducton In ths paper, I wll
More information2008/8. An integrated model for warehouse and inventory planning. Géraldine Strack and Yves Pochet
2008/8 An ntegrated model for warehouse and nventory plannng Géraldne Strack and Yves Pochet CORE Voe du Roman Pays 34 B1348 LouvanlaNeuve, Belgum. Tel (32 10) 47 43 04 Fax (32 10) 47 43 01 Emal: corestatlbrary@uclouvan.be
More informationGibbs Free Energy and Chemical Equilibrium (or how to predict chemical reactions without doing experiments)
Gbbs Free Energy and Chemcal Equlbrum (or how to predct chemcal reactons wthout dong experments) OCN 623 Chemcal Oceanography Readng: Frst half of Chapter 3, Snoeynk and Jenkns (1980) Introducton We want
More informationOptimal Choice of Random Variables in DITG Traffic Generating Tool using Evolutionary Algorithms
Optmal Choce of Random Varables n DITG Traffc Generatng Tool usng Evolutonary Algorthms M. R. Mosav* (C.A.), F. Farab* and S. Karam* Abstract: Impressve development of computer networks has been requred
More informationTHE LOAD PLANNING PROBLEM FOR LESSTHANTRUCKLOAD MOTOR CARRIERS AND A SOLUTION APPROACH. Professor Naoto Katayama* and Professor Shigeru Yurimoto*
7th Internatonal Symposum on Logstcs THE LOAD PLAIG PROBLEM FOR LESSTHATRUCKLOAD MOTOR CARRIERS AD A SOLUTIO APPROACH Professor aoto Katayama* an Professor Shgeru Yurmoto* * Faculty of Dstrbuton an Logstcs
More informationTwo Analytical Methods for Detection and Elimination of the Static Hazard in Combinational Logic Circuits
Crcuts and Systems,, 4, 46647 Publshed Onlne November (http//wwwscrporg/journal/cs) http//ddoorg/46/cs476 Two Analytcal Methods for Detecton and Elmnaton of the Statc Hazard n Combnatonal Logc Crcuts
More informationWeek 6 Market Failure due to Externalities
Week 6 Market Falure due to Externaltes 1. Externaltes n externalty exsts when the acton of one agent unavodably affects the welfare of another agent. The affected agent may be a consumer, gvng rse to
More informationESTABLISHING TRADEOFFS BETWEEN SUSTAINED AND MOMENTARY RELIABILITY INDICES IN ELECTRIC DISTRIBUTION PROTECTION DESIGN: A GOAL PROGRAMMING APPROACH
ESTABLISHIG TRADEOFFS BETWEE SUSTAIED AD MOMETARY RELIABILITY IDICES I ELECTRIC DISTRIBUTIO PROTECTIO DESIG: A GOAL PROGRAMMIG APPROACH Gustavo D. Ferrera, Arturo S. Bretas, Maro O. Olvera Federal Unversty
More informationThe eigenvalue derivatives of linear damped systems
Control and Cybernetcs vol. 32 (2003) No. 4 The egenvalue dervatves of lnear damped systems by YeongJeu Sun Department of Electrcal Engneerng IShou Unversty Kaohsung, Tawan 840, R.O.C emal: yjsun@su.edu.tw
More informationANALYZING 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, 6105194390,
More informationSOLVING CARDINALITY CONSTRAINED PORTFOLIO OPTIMIZATION PROBLEM BY BINARY PARTICLE SWARM OPTIMIZATION ALGORITHM
SOLVIG CARDIALITY COSTRAIED PORTFOLIO OPTIMIZATIO PROBLEM BY BIARY PARTICLE SWARM OPTIMIZATIO ALGORITHM Aleš Kresta Klíčová slova: optmalzace portfola, bnární algortmus rojení částc Key words: portfolo
More informationA. P. Sakis Meliopoulos Power System Modeling, Analysis and Control. Appendix B 1 Linear Programming 1
able of Contents from A. P. Sas Melopoulos Power Sstem Modelng, Analss and Control Append 1 Lnear Programmng 1.1 Introducton 1.2 Forms of Lnear Programmng Problems 1.3 Converson of Optmzaton Problems nto
More informationLogical Development Of Vogel s Approximation Method (LDVAM): An Approach To Find Basic Feasible Solution Of Transportation Problem
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME, ISSUE, FEBRUARY ISSN 77866 Logcal Development Of Vogel s Approxmaton Method (LD An Approach To Fnd Basc Feasble Soluton Of Transportaton
More informationSection B9: Zener Diodes
Secton B9: Zener Dodes When we frst talked about practcal dodes, t was mentoned that a parameter assocated wth the dode n the reverse bas regon was the breakdown voltage, BR, also known as the peaknverse
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationA Constant Factor Approximation for the Single Sink Edge Installation Problem
A Constant Factor Approxmaton for the Sngle Snk Edge Installaton Problem Sudpto Guha Adam Meyerson Kamesh Munagala Abstract We present the frst constant approxmaton to the sngle snk buyatbulk network
More information1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)
6.3 /  Communcaton Networks II (Görg) SS20  www.comnets.unbremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes
More informationResearch Article A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service
Hndaw Publshng Corporaton Dscrete Dynamcs n Nature and Socety Volume 01, Artcle ID 48978, 18 pages do:10.1155/01/48978 Research Artcle A Tme Schedulng Model of Logstcs Servce Supply Chan wth Mass Customzed
More informationAryabhata s Root Extraction Methods. Abhishek Parakh Louisiana State University Aug 31 st 2006
Aryabhata s Root Extracton Methods Abhshek Parakh Lousana State Unversty Aug 1 st 1 Introducton Ths artcle presents an analyss of the root extracton algorthms of Aryabhata gven n hs book Āryabhatīya [1,
More informationAn Integrated Approach of AHPGP and Visualization for Software Architecture Optimization: A casestudy for selection of architecture style
Internatonal Journal of Scentfc & Engneerng Research Volume 2, Issue 7, July20 An Integrated Approach of AHPGP and Vsualzaton for Software Archtecture Optmzaton: A casestudy for selecton of archtecture
More informationCan Auto Liability Insurance Purchases Signal Risk Attitude?
Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? ChuShu L Department of Internatonal Busness, Asa Unversty, Tawan ShengChang
More informationWhen Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services
When Network Effect Meets Congeston Effect: Leveragng Socal Servces for Wreless Servces aowen Gong School of Electrcal, Computer and Energy Engeerng Arzona State Unversty Tempe, AZ 8587, USA xgong9@asuedu
More informationCalculating 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 informationVOLTAGE stability issue remains a major concern in
Impacts of Mert Order Based Dspatch on Transfer Capablty and Statc Voltage Stablty Cuong P. guyen, Student Member, IEEE, and Alexander J. Flueck, Member, IEEE Abstract In ths paper, the goal s to nvestgate
More informationAPPLICATION 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. Saedocho
More informationNew Approaches to Support Vector Ordinal Regression
New Approaches to Support Vector Ordnal Regresson We Chu chuwe@gatsby.ucl.ac.uk Gatsby Computatonal Neuroscence Unt, Unversty College London, London, WCN 3AR, UK S. Sathya Keerth selvarak@yahoonc.com
More information6. EIGENVALUES AND EIGENVECTORS 3 = 3 2
EIGENVALUES AND EIGENVECTORS The Characterstc Polynomal If A s a square matrx and v s a nonzero vector such that Av v we say that v s an egenvector of A and s the correspondng egenvalue Av v Example :
More informationbenefit 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 informationOptimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm
Internatonal Journal of Grd Dstrbuton Computng, pp.175190 http://dx.do.org/10.14257/gdc.2014.7.6.14 Optmzaton odel of Relable Data Storage n Cloud Envronment Usng Genetc Algorthm Feng Lu 1,2,3, Hatao
More information