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dc.contributor.authorNonthachoti, Udomsri
dc.contributor.authorAthakorn, Kengpol
dc.contributor.authorIshii, Kazuyoshi
dc.contributor.authorShimada, Youishi
dc.date.accessioned2010-11-19T07:24:18Z
dc.date.available2010-11-19T07:24:18Z
dc.date.issued2010-11-19T07:24:18Z
dc.identifier.urihttp://repository.rmutp.ac.th/handle/123456789/691
dc.descriptionรายงานการวิจัย--มหาวิทยาลัยเทคโนโลยีราชมงคลพระนคร, 2553en_US
dc.description.abstractThe objective of this research is to design forecasting support models on demand of durian for domestic markets and export markets for durian gardeners, durian entrepreneurs of domestic markets and export markets and the Office of Agricultural Economics to plan durian demand conforming with domestic markets and export markets because of Production and marketing main problems (The Agricultural Information Center, The office of Agricultural Economics: 2008) such as over - much durian production, during production capital increased , farmers' durian sold price tended to be lower and lower, inefficient domestic market management and more export but cheaper price, therefore, after that, to design forecasting for the purpose in order that durian would not be over demand which is containing factors of the demand of durian fresh, durian frozen, durian paste and durian chips for domestic markets and export markets exported to Asia, America, Australia and Africa. The research involves historical collection data in the period of 2002 to 2008. The basic of forecast models are the designed and improved models using an intelligent knowledge-based approach beginning Moving average Deseasonalized Exponential smoothing Double exponential smoothing and Artificial neural network (ANNs) program within the model of new value Creation and comparative accuracy models. The evaluation result of forecasting durian demand showed that lowest MAPE of Deseasonlized models at 3 month was durian fresh durian frozen and durian paste but durian chips showed that lowest MAPE of ANNs at 4 input 10 hidden layers and 1 output was high accurate forecasting and optimal models. The analysis, recommendations and error forecast of durian demand are also presented.en_US
dc.description.sponsorshipRajamangala University of Technology Phra Nakhonen_US
dc.language.isoen_USen_US
dc.subjectMoving Averageen_US
dc.subjectdeseasonalizeden_US
dc.subjectartificial neural network(ANNs).en_US
dc.subjectExponential Smoothingen_US
dc.subjectdouble exponential smoothingen_US
dc.titleThe Design of a Forecasting Support Models on Demand of Durian for Domestic Markets and Export Markets by Time Series and ANNs.en_US
dc.typeResearch Reporten_US
dc.contributor.emailauthornonthachoti.u@rmutsb.ac.then_US
dc.contributor.emailauthornonthachoti.u@hotmail.comen_US
dc.contributor.emailauthorarit@rmutp.ac.then_US


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