The Design of a Forecasting Support Models on Demand of Durian for Domestic Markets and Export Markets by Time Series and ANNs.

Transcription

1 The 2 d RMUTP Ieraoal Coferece 2010 Page 108 The Desg of a Forecasg Suppor Models o Demad of Dura for Domesc Markes ad Expor Markes by Tme Seres ad ANNs. Udomsr Nohacho, 1* kegpol Ahakor, 2 Kazuyosh Ish, 3 Yoush Shmada. 4 *1 Deparme of Idusral Egeerg, Kg Mogku's Uversy of Techology Norh Bagkok, Bagkok, Thalad. 2 Deparme of Idusral Egeerg, Kg Mogku's Uversy of Techology Norh Bagkok, Bagkok, Thalad. 3 Deparme of Idusral ad socal Maageme Sysems,Kaazawa sue of Techology,Assa srucors,kaazawa sue of Techology, kaazawa,japa. 4 Deparme of Idusral ad socal Maageme Sysem from he feld of maageme ad busess archeecure,kaazawa sue of echology, Kaazawa,Japa. *Correspodg Auhor: ohacho.u@rmusb.ac.h, ohacho.u@homal.com Absrac The objecve of hs research s o desg forecasg suppor models o demad of dura for domesc markes ad expor markes for dura gardeers, dura erepreeurs of domesc markes ad expor markes ad he Offce of Agrculural Ecoomcs o pla dura demad coformg wh domesc markes ad expor markes because of Produco ad markeg ma problems (The Agrculural Iformao Ceer, The offce of Agrculural Ecoomcs: 2008) such as over - much dura produco, durg produco capal creased, farmers' dura sold prce eded o be lower ad lower, effce domesc marke maageme ad more expor bu cheaper prce, herefore, afer ha, o desg forecasg for he purpose order ha dura would o be over demad whch s coag facors of he demad of dura fresh, dura froze, dura pase ad dura chps for domesc markes ad expor markes expored o Asa, Amerca, Ausrala ad Afrca. The research volves hsorcal colleco daa he perod of 2002 o The basc of forecas models are he desged ad mproved models usg a ellge kowledge-based approach begg Movg average Deseasoalzed Expoeal smoohg Double expoeal smoohg ad Arfcal eural ework (ANNs) program wh he model of ew value Creao ad comparave accuracy models. The evaluao resul of forecasg dura demad showed ha lowes MAPE of Deseasolzed models a 3 moh was dura fresh dura froze ad dura pase bu dura chps showed ha lowes MAPE of ANNs a 4 pu 10 hdde layers ad 1 oupu was hgh accurae forecasg ad opmal models. The aalyss, recommedaos ad error forecas of dura demad are also preseed. Keyword: Movg Average, deseasoalzed, Expoeal Smoohg, double expoeal smoohg, arfcal eural ework(anns). Gree Techology ad Producvy

2 The 2 d RMUTP Ieraoal Coferece 2010 Page Iroduco Sce he pla of ecoomc ad socal developme of Thalad (year ), he Agrculure sascs of Thalad ad Basc Agrculural Ecoomy Daa year 2007 have show ha he agrculural produc was mpora o Tha ecoomy sysem. The worh of domesc marke was abou 2,941 mllo dollar, especally a dura whch was expored he secod whle he peapple was he mos. The expor dura was abou 88 mllo dollar per year (The cooperao of he offce of Agrculural Ecoomcs ad he cusoms year 2008.) The bgges area of plag dura he Eas of Thalad, for example, Chahabur, Rayog ad Trad ad he Souh of Thalad for example Chumpho, Suraha, ad Nakorsrhammaraj. Chahabur have produced 34 % of oal produco were he ma whch sources of dura produco of Thalad. (Basc Agrculural Ecoomcal Daa : 2006, 53) Suao of Dura Produco, dura produco durg las 6 year from , year 2003, he dura produco was 736,651 os, released domesc markes 628,713 os ad expor markes 107,028 os. I year 2008, he dura was produco 637,790 os, released domesc o markes 390,790 os ad expor markes 247,00 os. The dura produco year 2008 eded o crease because from year 2006 o year 2007, here was he projec o promoe ad develop dura produco he Eas ad he Souh so ha dura plag creased 14,286 Acre ad he area of produc was 382,819 Acres. The produc he Eas (Chaabur, Rayog, Trad) was gahered March - July (more dura Aprl - May), he Souh (Chumpor, Suraha, Nakorsrhammaraj), was gahered Jue - Ocober (more dura July - Augus).(The offce of Agrculural Ecoomcs: 2008).as show Fgure 1. Fgure 1 dura growg ad he produco area.(source :hp ://mages.google.co.h/mage : 2008) 1.1 Ma problems of Produco ad markeg (The Agrculural Iformao Ceer, The offce of Agrculural Ecoomcs: 2008) 1.1.1Dura frus were more harvesed he mddle of he seaso. More dura were harvesed smulaeously because The Eas cossg of Chahabur, Rayog ad Trad, harves perod was from March o July ad abuda produc perod was from Aprl o May. The Souh cossg of Chumpho, Suraha ad Nakho srhammaraj, harves perod was from Jue o Ocober ad abuda produc perod was from July o Augus The old gardes had lower effce produco. - The versed capal was used for old dura rees. - The expor markes o demad was Mhoog dura oly ad guaraee for GAP bu he farmer had few plag areas cerfed by Good Agrculural pracce(gap) of Deparme of Agrculure The domesc marke maageme was effce because he mpora areas are he Eas ad he Souh had problems of over-much dura produco ad cheaper prce dura The expor dura o expor markes creased bu was cheaper prce. Accordg o he suaoal problems of dura quay he demad domesc markes ad expor markes, here are few Gree Techology ad Producvy

3 The 2 d RMUTP Ieraoal Coferece 2010 Page 110 researches hs feld, gap of research ad he problems are o solved effcely so he research o cosruc he mehodology for a approprae desg of a forecasg suppor demad of dura for domesc markes ad expor markes s ecessary. The ew mehodology should be able o help markeg sysem effcely for forecasg a opmal demad dura for he purpose order ha dura domesc markes ad expor markes wll o be over demad. 1.2 These are he research quesos: sce prevous me ul prese, how have he forecasg models of dura demad bee domesc markes ad expor markes of hose forecas models? Wha s a approprae model for forecasg o dura demad o coform wh domesc markes ad expor markes? 1.3Ths sudy ams o mee he followg objecves: 1.3.1To desg of forecasg suppor models o demad of dura for domesc markes ad expor markes To pla o sales approprae dura fresh, dura froze, dura pase ad dura chps o coform o domesc markes ad expor markes To fds he resul of forecasg dura demad domesc markes ad expor markes for he offce of Agrculural Ecoomcs wh sakeholder. 2. Research Mehodology 2.1 Domesc ad foreg marke demad of dura fresh, dura froze, Dura pase ad dura chps wll be suded. The formao sources are Offce of Agrculural Ecoomcs, Garde plas Research Isue, Deparme of Agrculural Exeso, Offce of Agrculural Ecoomcs Research, Deparme of Goods ad Markeg Research, Deparme of Commercal Ecoomy, Deparme of Ieral Trade, Deparme of Expor Promoo, Cusoms Deparme ad ec. 2.2 The formao of dura fresh, froze dura, dehydraed dura ad dura preserve demad wll be suded. 2.3 Varables fluecg domesc ad foreg marke demad wll be researched. 2.4 The model of dura demad forecas wll be suded ad developed. 2.5 The forecas usg Tme seres models wll be suded as follows Movg Average Desesoalzed Expoeal Smoohg Double Expoeal Smoohg 2.6 The forecas usg Arfcal eural ework models be deermg 4 pu varables wll be suded as follows Ipu Varable1(Var1) s f dura fresh dura froze, dura pase ad dura chps expor prce Ipu Varable2(Var2)s ol prce Ipu Varable3 (Var3) s cosumer prce dex Ipu Varable4 (Var3) s exchage rae of Tha moey. 2.7 The model of dura forecas based o he ype of Back propagao of Arfcal eural ework wll be cosruced. 2.8 The model of dura forecas wll be esed by usg he formao from year 2002 ul The forecas usg arfcal eural ework ad usg Tme seres echque 2.10 Domesc ad Expor marke demad wll be aalyzed by deermg he approprae demad quay of dura fresh, dura froze, dura pase ad dura chps. 3. The Srucure of domesc markes ad expor markes ad Models. The Desg of a forecasg Suppor Sysem o Demad of Dura for Domesc Markes ad Expor Markes s show fgure 2 Gree Techology ad Producvy

4 The 2 d RMUTP Ieraoal Coferece 2010 Page 111 Dura pase. Dura chps. Fgure 3 The kds of dura for domesc markes ad expor markes. Fgure 2 he srucure markes ad logsc of domesc markes ad expor markes. The srucure markes ad logscs of domesc markes ad expor markes are show fgure1 Afer harvesg dura was raspored by ruck o he bgges agrculural markes Thalad whch are Talaadha ad Talaad Smumueag markes of domesc markes ad expor markes. The boh markes sells her goods her shops Dura frus are cu, graded ad purchased by rade ageces a he orchards. The ageces purchased were kds of dura from farmer o domesc markes for cosumers Thalad ad hey purchased dura fresh, dura froze for domesc markes o expor markes. The group sales purchased dura a he orchards o he facory o produce was dura pase ad dura chps o expor markes. Ther goods for sock purchasers s smaller sze/volume. The Talaadha marke s busy wh a umber of buyers a 24 hours ad Talaad Smumueag marke s busy wh a umber of buyers aroud 6 pm. The expor dura markeg sysem dura sale cosss of erepreeurs ad mddleme he kds of dura for domesc markes ad expor markes as show fgure 3 Dura fresh. Dura froze. 3.1 Modelg Forecas of Tme Seres ad Arfcal eural ework (ANNs). Modelg forecas of me seres ad Arfcal eural ework (ANNs) has bee oe of he ma research edeavors for decades. I he early 1920s, he decomposo model alog wh seasoal adjusme was he major research focus due o Persos (1919, 1923) work o decomposg a seasoal me seres. Hol (1957) ad wers (1960) developed mehod for forecasg red ad seasoal me seres based o he weghed expoeal smoohg. Ths model has performed well much real world applcao sad s sll oe of he mos wdely used Tme seres forecasg mehods. More recely, ANNs have bee wdely used as a powerful alerave o radoal me seres modelg (Zhag e al., 1998; Nelso e al., 1999; Hase ad Nelso, 2003). Whle her ably o model complex fucoal paers he daa has bee esed, her capably for modelg me seres s o sysemacally vesgaed. 3.2 Tme seres. Tme seres are forecasg echques by assumpo ha somehg was occurred he pass wll coue o he fuure. The mpora facor s he oly me. Forecasg mehods have may ypes such as, movg average, deseasoalzed, expoeal smoohg, double expoeal smoohg ec Movg Average model. The forecasg by movg average model o fd he average of dura demad he pas for a moh ad a year advace ha he mpora facor s dex we ca calculae by: show equao 1. Gree Techology ad Producvy

5 The 2 d RMUTP Ieraoal Coferece 2010 Page 112 m A = m = MA F (1) ( ) MA = Movg average of ( ) F + 1 forecased demad perod = he moh of forecas. m = he las moh ha perod use for calculag. = he frs moh ha perod a sar for calculag. = umber of moh movg average a from 2, 3, 4,6,8,9 ad 12 moh = kd of dura f = 1 dura fresh = 2 dura froze = 3 dura pase = 4 dura chps. A = acual demad perod Desesoalzed model. The forecasg by desesoalzed o fd he demad coformg wh seasoal chages ad dffereces each moh ad each year we calculae by: show equao2. m A = m + 1 D MA( ) p = (2) D MA( ) p = deseasoalzed movg average of for perod p. p = he perod of forecas for movg average f p=1 a sar for calculag from he frs moh o las moh of umber movg average f p=2 a sar for calculag from he secod moh o las moh of umber movg average. m = he las moh ha perod use for calculag. = he frs moh ha perod a sar for calculag. = umber of moh movg average a from 3, 6,ad 12 moh = kd of dura f = 1 dura fresh = 2 dura froze = 3 dura pase = 4 dura chps. A = acual demad perod. A RcD = (3) RcD = Rao ceered deseasoalzed m RcD S = (4) ma S = Seasoal dex ma = Toal of mohly average. m = umber of mohly A DF = (5) S DF = Deseasoalzed forecasg Expoeal smoohg model. The forecasg by expoeal smoohg model whch smoohed wh he movg daa ad he couerbalace usg he effcecy of smoohg (α) o smooh he gaed average o have he accurae forecas we calculae by: show equao.6. ESF (6) + 1 = αa + ( 1 α ) ESF ESF + 1 = Expoeal smoohg forecas of ex moh ha perod + 1. ESF = Expoeal smoohg forecas demad he each of perod = prese me whe he forecasg of value s calculaed -1,-2,-3... are he pas, +1,+2,+3 are he fuure. o α = smoohg cosa a opmal of kd of dura. = kd of dura f = 1 dura fresh = 2 dura froze = 3 dura pase = 4 dura chps. α = smoohg cosa whe 0 α 1 A = acual demad perod O = a opmal of α for expoeal smoohg. Gree Techology ad Producvy

6 The 2 d RMUTP Ieraoal Coferece 2010 Page Double Expoeal smoohg model. The forecasg by double Expoeal Smoohg mode whch couerbalaced he daa by usg he effcecy of smoohg α ad β o fd more accurae forecas of red ad seaso we calculae by: show equao 7. DESF + 1 = ESF T (7) + 1 where DESF + 1 = Double expoeal smoohg for ex moh ha perod + 1 ESF + = αa + ( 1 α ) ESF (6) 1 T + = β( F + F ) + ( 1 β ) T (8) 1 1 ESF + 1 = forecasg for ex moh ha perod + 1for expoeal smoohg T + 1 = red facor for ex moh ha perod + 1 for expoeal smoohg F = forecas demad of perod = kd of dura f = 1 dura fresh = 2 dura froze = 3 dura pase = 4 dura chps. A = acual demad perod o α = smoohg cosa a opmal of kd of dura. o β = smoohg cosa for red a opmal of kd of dura. T = expoeal smoohed red facor perod O = opmal of α ad β for double expoeal smoohg. α = smoohg cosa whe 0 1 α β = smoohg cosa for red whe 0 β Neural eworks model. The arfcal eural eworks have bee wdely used as a promsg mehod for me seres forecasg. (G.Peer adm Q, 2005). Neural ework are a class of flexble olear models ha ca dscover paers adapvely from he daa. Theorecally, has bee show ha gve a approprae umber of olear processg us, eural ework ca lear from experece ad esmae ay complex fucoal relaoshps wh hgh accuracy. Emprcally, eural merous successful applcaos have esablshed her role for paer recogos ad forecasg. Alhough may ypes of eural ework models have bee proposed, he mos popular for forecasg s back propagao eural ework model as show fgure 4 V 1 V 2 V 3 V 4 pu Hdde layer Fgure 4 Nework archecure for forecasg. F m Oupu 4. Research resuls Table 1 The resul of models comparg of MAPE for kds of dura Gree Techology ad Producvy

7 The 2 d RMUTP Ieraoal Coferece 2010 Page 114 Fgure 4 The resul of 5 models comparg of MAPE ad he kds of dura The research resul of forecas usg movg average model. The mea of forecas used were 2, 3, 4,6,8,9 ad 12 moh, respecvely. Whe we compare, he mea of 2 mohs was forecased as follow. whe was 2 mohs a dura froze lowes MAPE was 52.37%, dura pase was 74.78% ad dura fresh was % ad whe was 6 mohs a dura chps, he lowes MAPE was 86.02%,respecvely, he resul of forecas usg desesoalzed model. The mea of forecas used were 3,6 ad 12 moh, respecvely. Whe we compare, he mea of 3 mohs was forecased as follows. whe moh was 3 mohs a dura froze lowes MAPE was 9.98%, dura fresh was 19.45% ad whe he mes was 6 mohs a dura pase lowes MAPE was 8.47%,dura chps was 96.76%, respecvely, he resul of forecas usg Expoeal Smoohg model. The mea of forecas used were α bewee 0.0 o 1.0, respecvely. Whe we compareα, he mea of α a opmal was forecased as follow. Whe α was 1.0 a dura froze lowes MAPE was 42.92%, dura pase was 66.50% ad dura fresh was 82.25% ad whe α was 0.1 a dura chps he lowes MAPE was % respecvely, he resul of forecas usg by double expoeal smoohg model. The mea of forecas used were α ad β bewee 0.0 o 1.0, respecvely. Whe we compare α ad β, he mea of α ad β a opmal was forecased as follow. Whe α = 0. 6β = 1. 0 was dura froze he lowes MAPE was 42.91% show able 4, whe α = 0. 5β = 1. 0dura pase was 66.48% ad dura fresh was 82.14% show able 5,6 ad whe α = 0. 1β = 0. 1 a dura chps lowes MAPE was % respecvely ad he resul of forecas usg Arfcal eural ework (ANNs)model. The mea of forecas used were hdde layer bewee 8, 10 ad 14, respecvely. Whe we compare hdde layers, he mea of hdde layer a opmal was forecased as follows. Whe 8 hdde layer a dura fresh he lowes MAPE was 23.96%, whe 10 hdde layers a dura chps was 41.50%,dura froze was 41.85% ad dura pase was % respecvely as show able 1 ad fgure Coclusos Ths paper descrbes he appled models buldg ad aalyss ad resul of forecasg ad ral models for forecasg dura demad mohly of dura fresh dura froze dura pase ad dura chps for domesc markes ad expor markes by Movg average Deseasoalzed,Expoeal smoohg,double expoeal Smoohg ad Arfcal eural ework(anns) o use. The basc cocep desg ad mproved model a ellge kowledge based approach wh a me seres ad arfcal eural ework(anns) program wh he model of ew value creaed ad comparave accuracy models. The evaluao resul of forecasg dura demad program ad ral models for forecasg dura demad show ha he lowes MAPE of Deseasolzed model a 3 moh s dura fresh dura froze ad dura pase bu dura chps show ha MAPE lowes of ANNs a 4 pu 10 hdde layers ad 1 oupu was hgh accurae forecasg models whch wll gve forecasg demad he bes. Gree Techology ad Producvy

8 The 2 d RMUTP Ieraoal Coferece 2010 Page Ackowledgeme The research was suppored he daa from he offce Agrculural ecoomcs, he Agrculural formao ceer of Thalad durg The auhors also would lke o hak you very much he members of McGll uversy Caada ad Kaazawa sue of echology Japa research ework for her cooperao wh hs research projec. 7. Refereces. [1] Ajh Abraham Arfcal Neural Neworks. Oklahoma Sae Uversy, Sllwaer. [2] Berard W. Taylor III Iroduco o Maageme Scece Nh Edo. Prece Hall. [3] Boosarawogse, Rujrek., Forecasg Thalad s rce expor: Sascal echques vs. arfcal eural eworks. Compuers & dusral egeerg 53( ). [4] De Goojer, Ja G., Hydma, R.J., Years of me seres forecasg. Ieraoal Joural of Forecasg. 22( ). [5] Demuh, H. e al Neural Nework Toolbox 6 User s Gude. Nack,MA: The MahWorks,Ic. [6] D. S. Jayas, J. Palwal ad N. S. Vse Mul-layer Neural Neworks for Image Aalyss of Agrculural Producs. Deparme of Bosysems Egeerg, Uversy of Maoba. [7] Fause,Lauree.,1994. Fudameals of Neural Neworks Archecures, Algorhms, ad Applcaos. Eglewood Clffs, NJ, Prece-Hall. [8] G. Peer Zhag Neural Neworks Busess Forecasg. Idea Group, Hershey PA. [9] Hasa Merdu Comparso of arfcal eural ework ad regresso pedorasfer fucos for predco of sol waer. Faculy of Agrculure, Uversy,Kahramamaras, Turkey. [10] Kegpol, A., Desg of a decso suppor sysem o evaluae logscs dsrbuo ework Greaer Mekog Subrego Coures. Ieraoal Joural of Produco Ecoomcs, 115, [11] Kegpol, A., O Bre, C., The developme of a decso suppor ool for he seleco of advaced echology o acheve rapd produc developme. Ieraoal Joural of Produco Ecoomcs, 69, [12] Kegpol, A., Tuome, M., A framework for group decso suppor sysems: A applcao he evaluao of formao echology or logscs frms. Ieraoal Joural of Produco Ecoomcs, 101, [13] Lauree Fause Fudameals of Neural Neworks Archecures, Algorhms ad Applcaos. Prece-Hall, Eglewood Clffs. [14] Mddleo ad Mchael R Daa Aalyss usg Mcrosof Excel. Pacfc Grove, CA : Duxbury. [15] Meehom, W., Kegpol, A., Sudy o wegh of he assessme crera for Thalad Qualy Award. Ieraoal Coferece of Idusral Egeerg ad Egeerg Maageme, 9-11 December 2008, Sgapore. [16] Makrdakd, Spyros., Wheelwrgh, Seve C.,1983.Forecasg: Mehods ad Applcaos. [17] Sohl,Jeffrey.,Vekaachalam,A.R., A eural ework approach o Forecasg model seleco. Iformao & Maageme 29 ( ). [18] Smh, Kae.,Gupa, Jader.,2002. Neural Neworks Busess: Techques ad Applcaos. Hershey PA, Idea Group. [19] Spyros Makrdakd ad Seve C Forecasg: Mehods ad Applcaos 2. Joh Wley& Sos Gree Techology ad Producvy