Using of a fuzzy logic as one of the artificial intelligence models to increase the efficiency of the biological treatment ponds in wastewater treatment plants

Authors : Hussein ALNAJJAR, Osman ÜÇÜNCÜ

Pages : 85-94

View : 14 | Download : 7

Publication Date : 2021-12-31

Article Type : Research Paper

Abstract :One of the most essential variables in water quality management and planning appears to be biological treatment in wastewater treatment plants. This critical characteristic, however, is difficult to measure and takes a long time to produce accurate findings. Scientists have attempted to develop several strategies to solve these challenges. Artificial intelligence models are one such way it is feasible to monitor the treatment plants pollutant parameters and manage these pollution elements during processing more reliably and economically. The use of a fuzzy logic model to control biological wastewater treatment is proposed in this research. The objective of these software models is to predict future treatment problems, intervene in the facility quickly and effectively, reduce or eliminate environmental pollution, improve the ecosystem, and determine the treatment efficiency of the wastewater treatment plant by using fewer laboratory-scale reactors and pilot plants. This study aims to use artificial intelligence models insert ignore into journalissuearticles values(fuzzy logic model); to achieve the best biological treatment insert ignore into journalissuearticles values(BOD, TN and TP); while at the same time ensuring that the treated wastewater is within the standards. The model was generated using FL insert ignore into journalissuearticles values(MATLAB software was used to create the FL model);, and the model inputs are HRT, pH, temperature, F/M and BOD load to assess to which degree each of these variables affects BOD, TN and TP. The model outputs were within the acceptable wastewater quality standards according to the Turkish water pollution control regulation for the receiving environment of treated wastewater.
Keywords : Biological treatment, artificial intelligence models, fuzzy logic, treated wastewater, Biological Oxygen Demand, total nitrogen and total phosphorus