Neural network model for product end-of-life strategies

Jahau Lewis Chen; Jun Nan Wu

Neural network model for product end-of-life strategies

Jahau Lewis Chen, Jun Nan Wu

機械工程學系

研究成果: Paper › 同行評審

2 引文斯高帕斯（Scopus）

摘要

Neural network has the advantages of easily to use and feasible to non-linear problems with learning capability. The theory of End-of-Life Design Advisor (ELDA) is selected as the basic structure of back-propagation neural network to determine the useful strategy. Furthermore, self organize map neural network was selected to analyze the relation between each strategies. Hence, the trained neural networks can simulate the analysis mode of ELDA rapidly and offer the designer with an easy operation method in the relative research domain.

原文	English
頁面	159-164
頁數	6
出版狀態	Published - 2003 7月 17
事件	2003 IEEE International Symposium on Electronics and the Environment - Boston MA, United States 持續時間: 2003 5月 19 → 2003 5月 22

Other

Other	2003 IEEE International Symposium on Electronics and the Environment
國家/地區	United States
城市	Boston MA
期間	03-05-19 → 03-05-22

All Science Journal Classification (ASJC) codes

環境工程
廢物管理和處置
污染
電氣與電子工程

其它文件與鏈接

引用此

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title = "Neural network model for product end-of-life strategies",

abstract = "Neural network has the advantages of easily to use and feasible to non-linear problems with learning capability. The theory of End-of-Life Design Advisor (ELDA) is selected as the basic structure of back-propagation neural network to determine the useful strategy. Furthermore, self organize map neural network was selected to analyze the relation between each strategies. Hence, the trained neural networks can simulate the analysis mode of ELDA rapidly and offer the designer with an easy operation method in the relative research domain.",

author = "Chen, {Jahau Lewis} and Wu, {Jun Nan}",

year = "2003",

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language = "English",

pages = "159--164",

note = "2003 IEEE International Symposium on Electronics and the Environment ; Conference date: 19-05-2003 Through 22-05-2003",

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AU - Chen, Jahau Lewis

AU - Wu, Jun Nan

PY - 2003/7/17

Y1 - 2003/7/17

N2 - Neural network has the advantages of easily to use and feasible to non-linear problems with learning capability. The theory of End-of-Life Design Advisor (ELDA) is selected as the basic structure of back-propagation neural network to determine the useful strategy. Furthermore, self organize map neural network was selected to analyze the relation between each strategies. Hence, the trained neural networks can simulate the analysis mode of ELDA rapidly and offer the designer with an easy operation method in the relative research domain.

AB - Neural network has the advantages of easily to use and feasible to non-linear problems with learning capability. The theory of End-of-Life Design Advisor (ELDA) is selected as the basic structure of back-propagation neural network to determine the useful strategy. Furthermore, self organize map neural network was selected to analyze the relation between each strategies. Hence, the trained neural networks can simulate the analysis mode of ELDA rapidly and offer the designer with an easy operation method in the relative research domain.

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M3 - Paper

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EP - 164

T2 - 2003 IEEE International Symposium on Electronics and the Environment

Y2 - 19 May 2003 through 22 May 2003

ER -

Neural network model for product end-of-life strategies

摘要

Other

All Science Journal Classification (ASJC) codes

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