Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values
This paper proposes a generalized grey target decision method (GGTDM) with index and weight both containing mixed attribute values based on Kullback-Leibler (K-L) distance. The proposed approach builds the weight function converting the mixed attribute-based weights into the certain number-based wei...
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doaj-f4d5af57fa024a25805b938dae7731932021-03-30T03:23:04ZengIEEEIEEE Access2169-35362020-01-01816284716285410.1109/ACCESS.2020.30200459179767Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute ValuesJinshan Ma0https://orcid.org/0000-0002-2705-1241Xiaolin Ma1Jinmeng Yue2Di Tian3School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, ChinaSchool of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, ChinaSchool of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, ChinaSchool of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, ChinaThis paper proposes a generalized grey target decision method (GGTDM) with index and weight both containing mixed attribute values based on Kullback-Leibler (K-L) distance. The proposed approach builds the weight function converting the mixed attribute-based weights into the certain number-based weights and takes the comprehensive weighted K-L distance as the decision-making basis (DMB). The proposed approach conducts its task in the following steps. First, all indices of alternatives are converted into binary connection numbers. Second, the two-tuple (determinacy, uncertainty) numbers originated from index binary connection numbers are obtained. Third, the two-tuple (determinacy, uncertainty) numbers of target center are calculated. Following that the certain number-based weights are obtained by the weight function. Then the comprehensive weighted K-L distance of each alternative and its target center is calculated. And the final decision making is based on the value of comprehensive weighted K-L distance with which the smaller the better. A case study illustrates the proposed approach with its effectiveness of converting the uncertain weights into the certain weights and the accurate results comparing with other decision-making methods.https://ieeexplore.ieee.org/document/9179767/Kullback-Leibler distancemixed attributesgeneralized grey target decision methodbinary connection numberweight function |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jinshan Ma Xiaolin Ma Jinmeng Yue Di Tian |
spellingShingle |
Jinshan Ma Xiaolin Ma Jinmeng Yue Di Tian Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values IEEE Access Kullback-Leibler distance mixed attributes generalized grey target decision method binary connection number weight function |
author_facet |
Jinshan Ma Xiaolin Ma Jinmeng Yue Di Tian |
author_sort |
Jinshan Ma |
title |
Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values |
title_short |
Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values |
title_full |
Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values |
title_fullStr |
Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values |
title_full_unstemmed |
Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values |
title_sort |
kullback-leibler distance based generalized grey target decision method with index and weight both containing mixed attribute values |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
This paper proposes a generalized grey target decision method (GGTDM) with index and weight both containing mixed attribute values based on Kullback-Leibler (K-L) distance. The proposed approach builds the weight function converting the mixed attribute-based weights into the certain number-based weights and takes the comprehensive weighted K-L distance as the decision-making basis (DMB). The proposed approach conducts its task in the following steps. First, all indices of alternatives are converted into binary connection numbers. Second, the two-tuple (determinacy, uncertainty) numbers originated from index binary connection numbers are obtained. Third, the two-tuple (determinacy, uncertainty) numbers of target center are calculated. Following that the certain number-based weights are obtained by the weight function. Then the comprehensive weighted K-L distance of each alternative and its target center is calculated. And the final decision making is based on the value of comprehensive weighted K-L distance with which the smaller the better. A case study illustrates the proposed approach with its effectiveness of converting the uncertain weights into the certain weights and the accurate results comparing with other decision-making methods. |
topic |
Kullback-Leibler distance mixed attributes generalized grey target decision method binary connection number weight function |
url |
https://ieeexplore.ieee.org/document/9179767/ |
work_keys_str_mv |
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1724183590571343872 |