URBAN WASTEWATER TREATMENT PLANT EFFICIENCY MODELING WITH ARTIFICIAL NEURAL NETWORK: KONYA EXAMPLE

Abstract: With the climate crisis, the need to use our natural resources effectively and efficiently has begun to be discussed on the world agenda. The reality of drought that we are facing in this process has also brought to the agenda the development of appropriate technologies for the reuse of wastewater. In this context, it is important to control the process management of existing wastewater treatment plants, reduce the potential effects of wastewater treatment plant effluent on the receiving environment and make it reusable. With developing computer technologies, the use of artificial intelligence techniques has increased. Artificial neural networks are also included among these techniques. Studies are being carried out to predict the performance of urban wastewater treatment plants using methods such as artificial neural networks. In our study, it was aimed to estimate the values of Konya Urban Wastewater Treatment Plant effluent parameters using an artificial neural network model. By using the Wastewater Treatment Plant inlet water data, outlet water values can be predicted as a result of Artificial Neural Network modeling, thus predicting sudden changes that occur during the operation of wastewater treatment plants and situations requiring intervention will be important in preventing environmental risks. Additionally, time and cost will be saved. It will set an example for similar processes.