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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Main Authors: Jinshan Ma, Xiaolin Ma, Jinmeng Yue, Di Tian
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9179767/
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spelling 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/
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AT xiaolinma kullbackleiblerdistancebasedgeneralizedgreytargetdecisionmethodwithindexandweightbothcontainingmixedattributevalues
AT jinmengyue kullbackleiblerdistancebasedgeneralizedgreytargetdecisionmethodwithindexandweightbothcontainingmixedattributevalues
AT ditian kullbackleiblerdistancebasedgeneralizedgreytargetdecisionmethodwithindexandweightbothcontainingmixedattributevalues
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