An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making

The use of Choquet integral as an aggregation operator in multi-criteria decision-making problems requires the prior estimation of fuzzy measure values. λ0 -measure is one form of fuzzy measure which was introduced to reduce the usual computational complexity associated with the estimation of fuzzy...

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Main Authors: Krishnan, Anath Rau, Hamid, Rizal, Mat Kasim, Maznah
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/27240/1/ICIEA%202020%20969%20973.pdf
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author Krishnan, Anath Rau
Hamid, Rizal
Mat Kasim, Maznah
author_facet Krishnan, Anath Rau
Hamid, Rizal
Mat Kasim, Maznah
author_sort Krishnan, Anath Rau
collection UUM
description The use of Choquet integral as an aggregation operator in multi-criteria decision-making problems requires the prior estimation of fuzzy measure values. λ0 -measure is one form of fuzzy measure which was introduced to reduce the usual computational complexity associated with the estimation of fuzzy measure values. However, the existing techniques to estimate λ0 -measure require some amount of initial data from the decision-makers. This paper, therefore, aimed at proposing a completely unsupervised estimation technique, where the λ0- measure values are directly derived based on the available decision matrix, without the need for any initial data from the decision-makers. The technique was developed by incorporating the CRITIC method into the original λ0 - measure estimation technique. The usage of the proposed technique was illustrated based on a university course evaluation problem. The same problem was also solved with a conventional additive operator for the comparison purpose.
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spelling uum-272402020-07-23T02:53:17Z https://repo.uum.edu.my/id/eprint/27240/ An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making Krishnan, Anath Rau Hamid, Rizal Mat Kasim, Maznah QA75 Electronic computers. Computer science The use of Choquet integral as an aggregation operator in multi-criteria decision-making problems requires the prior estimation of fuzzy measure values. λ0 -measure is one form of fuzzy measure which was introduced to reduce the usual computational complexity associated with the estimation of fuzzy measure values. However, the existing techniques to estimate λ0 -measure require some amount of initial data from the decision-makers. This paper, therefore, aimed at proposing a completely unsupervised estimation technique, where the λ0- measure values are directly derived based on the available decision matrix, without the need for any initial data from the decision-makers. The technique was developed by incorporating the CRITIC method into the original λ0 - measure estimation technique. The usage of the proposed technique was illustrated based on a university course evaluation problem. The same problem was also solved with a conventional additive operator for the comparison purpose. 2020 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/27240/1/ICIEA%202020%20969%20973.pdf Krishnan, Anath Rau and Hamid, Rizal and Mat Kasim, Maznah (2020) An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making. In: 2020 IEEE 7th International Conference on Industrial Engineering and Applications, 16-18 April 2020, Bangkok. http://doi.org/10.1109/ICIEA49774.2020.9102098 doi:10.1109/ICIEA49774.2020.9102098 doi:10.1109/ICIEA49774.2020.9102098
spellingShingle QA75 Electronic computers. Computer science
Krishnan, Anath Rau
Hamid, Rizal
Mat Kasim, Maznah
An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
title An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
title_full An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
title_fullStr An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
title_full_unstemmed An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
title_short An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
title_sort unsupervised technique to estimate λ0 fuzzy measure values and its application to multi criteria decision making
topic QA75 Electronic computers. Computer science
url https://repo.uum.edu.my/id/eprint/27240/1/ICIEA%202020%20969%20973.pdf
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