| Summary: | 碩士 === 國立屏東科技大學 === 資訊管理系所 === 104 === The agricultural issue is always the critical factor to achieving the sustainability of a country. Due to the growing of plants is affected by weather, season, and lots of external influences, the harvest of crops is unstable and might cause the imbalance between supply and demand in the market. Therefore, the precise prediction of demand in the crops transaction market is important. It is helpful to the farmers to make the cultivating plan and also beneficial to the development of agriculture. In our research, we apply support vector machine (SVM) to develop a prediction model for transaction volume of crops in the auction market. We conducted different prediction models based on different prediction variables combinations. The results show that the price is the most significant variable in the prediction, and different crop should have different variable combinations. For example, for the prediction of pineapple and banana, the economic factors should be considered, and cabbage can have the most accurate prediction by only applying price as the prediction factor.
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