The research of compost quality evaluation modeling based on high speed and precise genetic algorithm neural network

Abstract

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 high speed and precise genetic algorithm neural network is presented. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP which has higher accuracy and faster convergence speed. 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. The experimental results show that the modeling method can truly evaluate the compost quality by learning the index information of sludge compost quality, and this method is feasible and effective.