ENHANCING SUSTAINABILITY INDEX PARAMETER USING ANFIS COMPUTATIONAL INTELLIGENCE MODEL

被引:0
作者
Septiyana, Diah [1 ,2 ]
Abd. Rahman, Mohamed [1 ]
Ariff, Tasnim Firdaus Mohamed [1 ]
Sukindar, Nor Aiman [1 ]
Adesta, Erry Yulian Triblas [3 ]
机构
[1] Int Islamic Univ Malaysia IIUM, Dept Mfg & Mat Engn, Kulliyyah Engn KOE, Selangor, Malaysia
[2] Univ Muhammadiyah Tangerang, Fac Engn, Dept Ind Engn, Banten, Indonesia
[3] Univ Indo Global Mandiri UIGM, Fac Engn, Dept Ind Engn Safety & Hlth, Palembang, Indonesia
来源
IIUM ENGINEERING JOURNAL | 2023年 / 24卷 / 02期
关键词
Sustainability Index; Computational Intelligence; ANFIS; Weightage; Water Industry; WATER SUSTAINABILITY; HYDROLOGY;
D O I
10.31436/iiumej.v24i2.2810
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The scarcity of water resource is an essential global issue in the 21st century. Therefore, one of the Sustainable Development Goals (SDG) was to ensure the availability and sustainable management of water and sanitation. To do this, it is necessary to assess whether or not the SDG has been followed using the sustainability index. However, there are a lot of sustainability indexes and many of them have the same problem, in which all sustainability index parameters have the same weightage. This problem shows us that every parameter in the sustainability index is equal, while in real life there is no equal parameter. In this paper a weightage for each parameter is proposed to enhance the sustainability index. The method to assess the sustainability index parameters was using a questionnaire by key experts in the water industry. Using ANFIS computational intelligence, the result of the assessment was then fit to the frequent parameters that exist in other sustainability indexes. This proposed method can produce a ranking and weight for each sustainability index parameter and criteria. Using this method, the weightage for each sustainability index parameter can be generated, such as environmental 0.301, engineering 0.214, economic 0.280, and social 0.205.
引用
收藏
页码:258 / 268
页数:11
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