文献类型：会议论文

英文题名：The Research of Compost Quality Evaluation Modeling Based on High Speed and Precise Genetic Algorithm Neural Network

作者：Tian, Jingwen[1,2];Gao, Meijuan[1,2];Liu, Yanxia[1];Zhang, Fan[2]

第一作者：Tian, Jingwen

通讯作者：Tian, JW[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China;[2]Beijing Univ Chem Technol, Sch Informat Sci, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：IEEE International Conference on Industrial Technology

会议日期：APR 21-24, 2008

会议地点：Chengdu, PEOPLES R CHINA

语种：英文

外文关键词：Genetic algorithms; Neural networks; Sludge compost; Quality evaluation; Modeling

摘要：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.