Soft Measurement Modeling Based on High Speed and Precise Genetic Algorithm Neural Network for Sewage Treatment

Considering the issues that the sewage treatment process is a complicated and nonlinear system, it is very difficult to found the process model to describe it, and the key parameters of sewage treatment quality can not, be detected on-line, a soft measurement modeling method based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, the soft measurement modeling method can truly detect and assess the quality of sewage treatment in real time by learning the sewage treatment parameter information of sensors acquired. The experimental results show that this method is feasible and effective.