The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries
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...
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ndltd-TW-090NKIT56780042015-10-13T10:21:17Z http://ndltd.ncl.edu.tw/handle/35164828130673359884 The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries 應用模糊類神經法於建構全球運籌模式之決策-以台灣電子資訊業為例 Cheng-Wei Lin 林呈衛 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. Kune-Muh Tsai Jiuh-Biing Sheu 蔡坤穆 許鉅秉 2002 學位論文 ; thesis 106 zh-TW |
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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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Kune-Muh Tsai |
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Kune-Muh Tsai Cheng-Wei Lin 林呈衛 |
author |
Cheng-Wei Lin 林呈衛 |
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Cheng-Wei Lin 林呈衛 The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries |
author_sort |
Cheng-Wei Lin |
title |
The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries |
title_short |
The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries |
title_full |
The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries |
title_fullStr |
The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries |
title_full_unstemmed |
The Application of Fuzzy Neural Network to Establishment Policy of Global Logistics Operation Mode for Taiwan’s Electronic and Information Industries |
title_sort |
application of fuzzy neural network to establishment policy of global logistics operation mode for taiwan’s electronic and information industries |
publishDate |
2002 |
url |
http://ndltd.ncl.edu.tw/handle/35164828130673359884 |
work_keys_str_mv |
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