Forecasting of effluent from wastewater treatment industries using a novel Fuzzy logic system

Abstract

Accurate modelling of the wastewater discharge parameters is necessary to lower the operational costs of such a wastewater treatment facility. The article presents a unique method for predicting the effluent prominence features for such an industrialized wastewater treatment facility. Artificial intelligence modelling is one such technique that enables analysis of the pollutant characteristics in treatment facilities and more effective regulation of them during processing. The study suggests using a fuzzy logic approach to regulate biological wastewater treatment. These computer programs are designed to forecast treatment issues in the future intervene promptly and efficiently in the facility, lessen or completely eradicate environmental pollution, enhance the ecosystem, and assess the wastewater treatment plant's treatment efficiency. The study intends to employ fuzzy logic models of artificial intelligence to accomplish the best treatment process, including O&G, BOD, COD, TSS, and TDS, while also assuring that the treated wastewater complies with regulations. Additionally, statistical analysis of the data was performed. The best value and the highest R2 value were discovered; these numbers demonstrate that the expected and investigational performances are comparable, and that the plant's presentation could be correctly predicted utilizing a fuzzy logic model, allowing fuzzy logic to be employed to describe the method.