The Study of Compost Quality Evaluation Modeling Method Based on Wavelet Neural Network for Sewage Treatment

Because of the complicated interaction of the sludge compost components, it makes the compost quality evaluation system appear the non-linearity and uncertainty. According to the physical circumstances of sludge compost, a compost quality evaluation modeling method based on wavelet neural network is presented. We adopt a method of reduce the number of the wavelet basic function by analysis the sparse property of sample data, and use the learning algorithm based on gradient descent to train network. We select the index of sludge compost quality and take the high temperature duration, degradation rate, nitrogen content, average oxygen concentration and maturity degree as the evaluation parameters. With the ability of strong self-learning and function approach and fast convergence rate of wavelet neural network, the modeling method can truly evaluate the compost quality by learning the index information of sludge compost quality. The experimental results show that this method is feasible and effective.