An artificial neural network model in economic forecasting: A study in Thailand's natural rubber industry

• Main Authors: Arit Thammano, Rawin Raviwongse, Monticha Tanatammatid
• Other Authors: King Mongkut's Institute of Technology Ladkrabang
• Format: Article
• Published: 2018
• Subjects: Computer Science
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/18350
• Institution: Mahidol University

In the past forty years, the world demand for rubber, both natural and synthetic, as raw material has increased drastically. However, the use of natural rubber in industry has been declining due to several reasons such as unreliable quality, delayed delivery time, and fluctuating prices. Since Thailand is among the top three natural rubber producers in the world, in addition to the need to promote the use of natural rubber, the country must also improve its competitive edge in exporting them over other exporters. As such, one way to support the improvement is to develop a reliable model to forecast the demand and supply of natural rubber in the world market. In this study, an artificial neural network technique is applied to (i) study and forecast the world demand of natural rubber by region and (ii) estimate the appropriate export quantity for Thailand's natural rubber industry. The output from the neural network model can be directly applied to the economic planning for Thailand's natural rubber industry.