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

• 發表在: MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES
• Main Authors: Shafie, Muhammad Asyran; Mohamad, Daud; Kechil, Seripah Awang
• 格式: Article
• 語言: English
• 出版: PENERBIT UTM PRESS 2023
• 主題: Science & Technology - Other Topics
• 在線閱讀: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001117806300017

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.