期刊
COMPUTERS AND ELECTRONICS IN AGRICULTURE
卷 118, 期 -, 页码 259-269出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compag.2015.09.002
关键词
Longan supply forecasting; Fuzzy neural network; Support vector regression; Fuzzy support vector regression
资金
- Higher Education Research Promotion
- National Research University Project of Thailand
- Excellence Center in Logistics and Supply Chain Management, Chiang Mai University
- Office of the Higher Education Commission
An over-supply crisis in longans in northern Thailand adversely affected farmer income. Cultivating longans off-season was adapted as an alternative solution to this over-supply problem. However, lacking information management and analysis, over supply occurred even during the off-season, leading to a slump in the sale price. Supply forecasting plays an important role in solving this problem. To solve this problem, we proposed a systematic approach for off-season longan forecasting using neural network, fuzzy neural network, support vector regression and Fuzzy Support Vector Regression (FSVR). In addition, grid search was applied to each support vector model to find its optimum architecture. Real data sets were used to evaluate and compare the effectiveness and efficiency of the algorithms. The experimental results showed that FSVR was the most effective forecasting technique. (C) 2015 Elsevier B.V. All rights reserved.
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