Evidence based decision analysis and support

Jian Bo Yang; Dong Ling Xu

doi:10.1109/CICA.2011.5945764

Evidence based decision analysis and support

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this paper, the link and difference between the ER algorithm and Dampster's combination rule are analysed first. A new alternative ranking method is then investigated as an integrated part of the enhanced ER approach. © 2011 IEEE.

Original language	English
Title of host publication	IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation\|IEEE SSCI - Symp. Ser. Comput. Intell. - CICA - IEEE Symp. Comput. Intell. Control Autom.
Pages	131-136
Number of pages	5
DOIs	https://doi.org/10.1109/CICA.2011.5945764
Publication status	Published - 2011
Event	Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011 - Paris Duration: 1 Jul 2011 → …

Conference

Conference	Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011
City	Paris
Period	1/07/11 → …

Keywords

Evidential Reasoning approach
IDS
Intelligent Decision System
multiple criteria decision analysis
uncertainty

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10.1109/CICA.2011.5945764

Cite this

Yang, J. B., & Xu, D. L. (2011). Evidence based decision analysis and support. In IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation|IEEE SSCI - Symp. Ser. Comput. Intell. - CICA - IEEE Symp. Comput. Intell. Control Autom. (pp. 131-136) https://doi.org/10.1109/CICA.2011.5945764

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title = "Evidence based decision analysis and support",

abstract = "The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this paper, the link and difference between the ER algorithm and Dampster's combination rule are analysed first. A new alternative ranking method is then investigated as an integrated part of the enhanced ER approach. {\textcopyright} 2011 IEEE.",

keywords = "Evidential Reasoning approach, IDS, Intelligent Decision System, multiple criteria decision analysis, uncertainty",

author = "Yang, {Jian Bo} and Xu, {Dong Ling}",

year = "2011",

doi = "10.1109/CICA.2011.5945764",

language = "English",

isbn = "9781424499038",

pages = "131--136",

booktitle = "IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation|IEEE SSCI - Symp. Ser. Comput. Intell. - CICA - IEEE Symp. Comput. Intell. Control Autom.",

note = "Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011 ; Conference date: 01-07-2011",

}

Yang, JB & Xu, DL 2011, Evidence based decision analysis and support. in IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation|IEEE SSCI - Symp. Ser. Comput. Intell. - CICA - IEEE Symp. Comput. Intell. Control Autom.. pp. 131-136, Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011, Paris, 1/07/11. https://doi.org/10.1109/CICA.2011.5945764

Evidence based decision analysis and support. / Yang, Jian Bo ; Xu, Dong Ling.
IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation|IEEE SSCI - Symp. Ser. Comput. Intell. - CICA - IEEE Symp. Comput. Intell. Control Autom.. 2011. p. 131-136.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this paper, the link and difference between the ER algorithm and Dampster's combination rule are analysed first. A new alternative ranking method is then investigated as an integrated part of the enhanced ER approach. © 2011 IEEE.

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Evidence based decision analysis and support

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