A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification

A generalised L-R intuitionistic fuzzy numbers is an L-R intuitionistic fuzzy numbers that incorporates confidence level for both membership and non-membership functions. Therefore, this intuitionistic fuzzy number is suitable for classifying the river water pollution. This study aims to introduce t...

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Published in:MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES
Main Authors: Shafie, Muhammad Asyran; Mohamad, Daud; Kechil, Seripah Awang
Format: Article
Language:English
Published: PENERBIT UTM PRESS 2023
Subjects:
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001117806300015
author Shafie
Muhammad Asyran; Mohamad
Daud; Kechil
Seripah Awang
spellingShingle Shafie
Muhammad Asyran; Mohamad
Daud; Kechil
Seripah Awang
A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
Science & Technology - Other Topics
author_facet Shafie
Muhammad Asyran; Mohamad
Daud; Kechil
Seripah Awang
author_sort Shafie
spelling Shafie, Muhammad Asyran; Mohamad, Daud; Kechil, Seripah Awang
A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES
English
Article
A generalised L-R intuitionistic fuzzy numbers is an L-R intuitionistic fuzzy numbers that incorporates confidence level for both membership and non-membership functions. Therefore, this intuitionistic fuzzy number is suitable for classifying the river water pollution. This study aims to introduce the generalised L-R intuitionistic fuzzy numbers (GLRIFNs) which includes the membership and non-membership functions to classify the river water pollution using TOPSIS with CRITIC method. Due to the insufficient river data, this study has simulated the river data using the bootstrap method. This study had classified river water pollution for several rivers in Johor, Malaysia, namely Kim Kim River, Sayong River, Telor River, Pelepah River, and Bantang River from 2017 to 2021. The result shows that the Bantang River is the cleanest river, while the Kim Kim River is the most polluted river. The results proved that the GLRIFNs is quite a reliable method to classify river water pollution.
PENERBIT UTM PRESS
2289-5981
2289-599X
2023
19
6
10.11113/mjfas.v19n6.3105
Science & Technology - Other Topics
gold
WOS:001117806300015
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001117806300015
title A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
title_short A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
title_full A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
title_fullStr A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
title_full_unstemmed A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
title_sort A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification
container_title MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES
language English
format Article
description A generalised L-R intuitionistic fuzzy numbers is an L-R intuitionistic fuzzy numbers that incorporates confidence level for both membership and non-membership functions. Therefore, this intuitionistic fuzzy number is suitable for classifying the river water pollution. This study aims to introduce the generalised L-R intuitionistic fuzzy numbers (GLRIFNs) which includes the membership and non-membership functions to classify the river water pollution using TOPSIS with CRITIC method. Due to the insufficient river data, this study has simulated the river data using the bootstrap method. This study had classified river water pollution for several rivers in Johor, Malaysia, namely Kim Kim River, Sayong River, Telor River, Pelepah River, and Bantang River from 2017 to 2021. The result shows that the Bantang River is the cleanest river, while the Kim Kim River is the most polluted river. The results proved that the GLRIFNs is quite a reliable method to classify river water pollution.
publisher PENERBIT UTM PRESS
issn 2289-5981
2289-599X
publishDate 2023
container_volume 19
container_issue 6
doi_str_mv 10.11113/mjfas.v19n6.3105
topic Science & Technology - Other Topics
topic_facet Science & Technology - Other Topics
accesstype gold
id WOS:001117806300015
url https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001117806300015
record_format wos
collection Web of Science (WoS)
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