| Summary: | 碩士 === 國立高雄第一科技大學 === 運輸倉儲營運所 === 90 === ABSTRACT
This study is to classify the operation mode of enterprise global logistics and analyze what kinds of factors emphasized by different operation mode in order to establish a forecast model of global logistics management. Integrating fuzzy inference systems and neural network created this forecast model. First, we use fuzzy multiple attribute decision-making (FMADM) methods to gain fuzzy rules, then applicate Sugeno fuzzy inference systems to transfer fuzzy rules to neural network. Second, this neural network will be able to forecast what enterprise suits what operation mode through complete learning, training, and test. Finally, the proposed neural network can replace FMADM cumbersome computations, and assist follow-up decision maker to decide alternatives.
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