A systematic investigation of multi-attributive border approximation area comparison approach with Gaussian membership function for optimizing water quality

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dc.authoridPamucar, Dragan/0000-0001-8522-1942
dc.contributor.authorYasin, Yasir
dc.contributor.authorDemir, Gulay
dc.contributor.authorRiaz, Muhammad
dc.contributor.authorAslam, Muhammad
dc.contributor.authorPamucar, Dragan
dc.date.accessioned2025-05-04T16:47:25Z
dc.date.available2025-05-04T16:47:25Z
dc.date.issued2024
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractEnsuring the safety of drinking water is of utmost importance for the well-being of the general population. This study presents a new framework to assist specialists in selecting and assessing water samples, dealing with the urgent requirement for accurate and consistent analysis of water quality. We utilize the Gaussian Membership Function (GMF) to handle the inherent uncertainty in a dataset of 3276 samples obtained from Kaggle. The criteria importance through the inter-criteria correlation (CRITIC) technique is employed to evaluate and rank the significance of several criteria. We use the weighted aggregate sum product assessment (WASPAS) and multi-attributive border approximation area comparison (MABAC) methods to rank the water samples. Each technique has a comprehensive pseudocode to support it, which offers clear instructions for putting it into practice on various datasets. A comparative analysis confirms the efficacy and computational efficiency of these methods, showcasing their ability to improve assessments of water quality greatly. This research not only creates a strong and practical foundation for decision-making in water quality analysis but also adds to the progress of techniques. The acquired insights provide useful guidance for future research, potentially impacting the establishment of optimal methods in the evaluation of water quality.
dc.description.sponsorshipDeanship of Scientific Research at King Khalid University; Saudi Arabia [R.G. P-2/187/45]
dc.description.sponsorshipThe authors extend their appreciation to the Deanship of Scientific Research at King Khalid University, Abha 61413, Saudi Arabia for funding this work through the research groups program under grant number R.G. P-2/187/45.
dc.identifier.doi10.1007/s10668-024-05704-0
dc.identifier.issn1387-585X
dc.identifier.issn1573-2975
dc.identifier.scopus2-s2.0-85213043529
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1007/s10668-024-05704-0
dc.identifier.urihttps://hdl.handle.net/20.500.12418/35617
dc.identifier.wosWOS:001383446400001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofEnvironment Development and Sustainability
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250504
dc.subjectOptimising water quality
dc.subjectFuzzy modelling
dc.subjectGaussian membership function
dc.subjectCRITIC
dc.subjectWASPAS
dc.subjectMABAC
dc.subjectPseudocode
dc.titleA systematic investigation of multi-attributive border approximation area comparison approach with Gaussian membership function for optimizing water quality
dc.typeArticle

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