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A decision-theoretic framework for wastewater treatment performance assessment based on a fuzzy parameterized fuzzy
Muhammad Haris Saeed1, Fatima Razaq2, Muhammad Saeed2
1Department of Chemistry, University of Management and Technology, 54700, Lahore, Punjab, Pakistan.
None:
The economic development of a country is profoundly influenced by how it protects and utilizes its natural resources, one of which is wastewater, with emphasis on environmental sustainability. For this multi-factorial sustainability analysis, this study introduces a novel Fuzzy Parameterized Fuzzy Hypersoft Set (FPFHSS) structure to develop a comprehensive decision-making and performance evaluation system for wastewater treatment facilities. The practicality of the designed system is explored by highlighting its ability to evaluate urban projects and work as a decision-making system for environmental policy design. The study introduces an algorithm based on the hypersoft structure, allowing the division of attributes into sub-attributes for a more concise analysis. The sub-parametric values are first parameterized into fuzzy numbers and then evaluated based on their relative importance. With proper fuzzy parameterization of each sub-attribute, novel specialized FPFHSS based Technique of Ordered Preference Similar to Ideal Solution (TOPSIS) and Multi-Objective Optimization on the basis of a Ratio Analysis (MULTIMOORA) approaches are developed that provide a versatile analysis in addition to the newly developed algorithm. With these 3 specialized systems, 4 case studies were developed based on 19 pseudo-realistic environmental, social, technical, and economic factors each simulating a different scenario faced by nations highlighting sustainability, technical performance and the environment allowing for informed decision-making while addressing uncertainty making them highly suitable as a computational AI solution for real-data analysis. This fuzzy analysis offers a reference for making informed decisions in the context of environmental remediation and complex scenario simulations.
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