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硫酸盐废水处理中SRB生态因子的GA-NN建模研究
引用本文:徐岩,王爱杰,孙晓君,赵珣宇. 硫酸盐废水处理中SRB生态因子的GA-NN建模研究[J]. 科技导报(北京), 2007, 25(7): 33-35
作者姓名:徐岩  王爱杰  孙晓君  赵珣宇
作者单位:哈尔滨理工大学化学与环境工程学院,哈尔滨,150040;哈尔滨工业大学市政环境工程学院,哈尔滨,150090
基金项目:国家自然科学基金项目(59978012)
摘    要:利用产酸-硫酸盐还原反应器对高浓度硫酸盐废水进行处理时,硫酸盐还原菌的生态位是该系统的核心问题。将神经网络与遗传算法有机地结合起来,以神经网络为理论基础,利用遗传算法优化网络中的连接权值,对产酸硫酸盐还原反应系统进行建模与仿真化,并将之与采用回归分析法的模拟结果相对比。研究结果表明采用遗传算法优化神经网络的效果较好,所建模型的运算结果更为可靠。

关 键 词:高浓度硫酸盐废水  遗传算法  BP神经网络  硫酸盐还原菌  限制性生态因子
文章编号:1000-7857(2007)07-0033-03
修稿时间:2006-12-20

Investigation on Modeling of Ecological Factors of SRB in the Treatment of Sulfate Wastewater with GA-NN
XU Yan,WANG Aijie,SUN Xiaojun,ZHAO Xunyu. Investigation on Modeling of Ecological Factors of SRB in the Treatment of Sulfate Wastewater with GA-NN[J]. Science & Technology Review, 2007, 25(7): 33-35
Authors:XU Yan  WANG Aijie  SUN Xiaojun  ZHAO Xunyu
Affiliation:1. School of Chemistry and Enviroment Engineering, Harbin University of Science and Technology, Harbin 150040, China; 2. School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China
Abstract:The niche of SRB is a key factor in the sulfate wastewater treatment in acidogenic-desulfate reactor. In this paper, the weights of jointing in the network are optimized with Genetic Algorithms on the basis of BPNN(Back-Propagation Neural Network) and the model . Emulation of the acidogenic-desulfate reducing system is also made by combining Back Propagation Neural Network with Genetic Algorithms. The investigation shows that the mean error obtained from GA (Genetic Algorithms) model is more accurate and credible than that from RA (Regression Analysis) model .
Keywords:high concentration sulfate wastewater  Genetic Algorithms (GA)  Back-Propagation Neural Network (BPNN)  Sulfate Reducing Bacteria(SRB)  restrictive ecological factors
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