Page Header

An Application of Forecasting Models for the Supply and Demand Management of Cassava Products

Natthaya Choosuk, Athakorn Kengpol

Abstract


The objectives of this research are to generate models that can effectively forecast the supply and demand of four cassava products. The appropriate forecasting models for cassava production volume is Back Propagation Neural Network (BPN) 4-14-1, cassava starch is BPN 7-12-1, cassava chip is BPN 7-14-1, cassava pellets is Multiple Linear Regression (MLP), and sago is BPN 7-13-1. Then, Linear Programming is used to calculate the optimization of cassava products to obtain the maximum profit and for cassava plant areas to obtain the maximum yield per area. The benefits of this research can support management planning for farmers and manufacturers.

 


Keywords



Full Text: PDF

Refbacks

  • There are currently no refbacks.


Copyright © 2014 by King Mongkut’s University of Technology North Bangkok. All rights reserved.