Price Forecasting in the Public Agricultural Rubber Industry in Thailand: A Preliminary Investigation
Faculty of Computing, Health and Science
School of Computer and Security Science
Rubber latex price trend data in the public agricultural rubber industry in Thailand (PARIT) provide very useful information for policy development and implementation by government and non-government agencies and agriculturists in Thailand. They are used to give direction and aid planning for agricultural development and problem solving policy. However, they are affected by demand, supply, economic and political factors in local and global markets; causing price fluctuations and difficulties for policy development and implementation. Hence, forecasting is introduced to this industry as an alternative to predict suitable future trend data for policy makers. A broader study investigated a feasible newly refined rubber latex price forecasting model, with three variations, i.e., one year forecasting, six month forecasting and four month forecasting, each applying either non-neural or neural network training techniques. In this paper, experimental forecasting results are compared with actual rubber latex prices to determine forecasting accuracy and the feasible best-fitting model for policy makers in PARIT.