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Fuzzy inference optimization algorithms for enhancing the modelling accuracy of wastewater quality parameters
Taher Abunama1, Mozafar Ansari2, Oluyemi Olatunji Awolusi1
1Institute for Water and Wastewater Technology, Durban University of Technology, Durban, PO Box, 1334, South Africa.
Journal of Environmental Management
|May 28, 2021
Summary
Optimizing wastewater treatment plant (WWTP) models is crucial for environmental safety. A hybrid Particle Swarm Optimization-Genetic Algorithm (PSO-GA) showed superior performance in modeling effluent quality parameters compared to individual algorithms.
Area of Science:
- Environmental Engineering
- Computational Intelligence
- Water Quality Management
Background:
- Accurate modeling of wastewater treatment plants (WWTPs) is essential for safe environmental discharge.
- Metaheuristic optimization algorithms integrated with Fuzzy Inference Systems (FIS) offer a promising approach to enhance modeling accuracy.
Purpose of the Study:
- To evaluate the effectiveness of four population-based algorithms (PSO, GA, hybrid PSO-GA, M-IWO) integrated with FIS for modeling WWTP effluent quality.
- To compare the performance of these algorithms in predicting key wastewater parameters.
Main Methods:
- Integration of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), a hybrid PSO-GA, and Mutating Invasive Weed Optimization (M-IWO) with Fuzzy Inference Systems (FIS).
- Application of the integrated models to a full-scale WWTP in South Africa.
- Modeling of six effluent parameters: Alkalinity (ALK), Sulphate (SLP), Phosphate (PHS), Total Kjeldahl Nitrogen (TKN), Total Suspended Solids (TSS), and Chemical Oxygen Demand (COD).
Main Results:
- The hybrid PSO-GA algorithm demonstrated superior performance over individual PSO and GA in modeling all tested wastewater effluent parameters.
- PSO showed better performance than GA for Sulphate (SLP) and Total Kjeldahl Nitrogen (TKN) modeling.
- The Mutating Invasive Weed Optimization (M-IWO) algorithm did not achieve acceptable convergence for the studied parameters.
Conclusions:
- Three of the four evaluated algorithms, particularly the hybrid PSO-GA, significantly enhance the modeling accuracy of wastewater quality parameters.
- The integration of advanced optimization techniques with FIS is a viable strategy for improving WWTP performance monitoring and management.
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