PREDICTION AND DIAGNOSIS OF EXTRAORDINARY SITUATIONS FOR WASTEWATER TREATMENT SYSTEMS USING NEURAL NETWORK APPROACH.

The operation quality of a wastewater treatment system influences its effluent quality, treatment cost, and performance stability. The aim of this research is to aid wastewater plants surpass extraordinary situations by using a neural network approach leading to an early warning system. Sensitivity analysis methods are proposed to evaluate influence and time interval. The factor majorly influencing the effluent quality is the recycle ratio, which has the fastest response time and can be selected as a crucial operational variable for the optimal dynamic operation of the wastewater treatment system. The results show that the use of statistical methods, network experiment designs, and sensitivity analyses of input or output variables of wastewater treatment plants can successfully build a wastewater prediction model. [ABSTRACT FROM AUTHOR]