| Summary: | 碩士 === 淡江大學 === 資訊管理研究所 === 83 === The major purpose of this study is applying Genetic Algorithms(GAs) to developing fuzzy forecasting in order to increase the accuracy of forecasting. Genetic algorithm is a parallel goal-oriented search technique for optimization and can be used to easily find out the global or nearly global optima for optimization problems. In this study, we focus on sales forecasting and propose a dynamic forecasting model by using Genetic Algorithms in searching the optimal linguistic variables and partition intervals, and finding out the most fitness model basis w of fuzzy time series in different cases. Finally, we propose adding the expert opinions served as leading indicators in the fuzzy time series for forecsting value. Results show that the accuracy of the forecasting results is significantly improved, it proved the effectiveness of the fuzzy forecasting model we proposed.
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