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《Journal of Beijing University of Technology》 2012-01
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Flux Prediction of MBR Based on PSO-BP Neural Network

LIU Zhi-feng1,PAN Dan1,WANG Jian-hua1,YANG Shuang-xi2(1.College of Mechanical Engineering and Applied Electronics Technology,Beijing University of Technology,Beijing 100124,China; 2.College of Water Sciences,Beijing Normal University,Beijing 100875,China)  
Membranes fouling in MBR process is caused by many complex and interactional factors.A flux prediction model is put forward based on the PSO-BP neural network,which adjusts weights of BP neural network using particle swarm optimization(PSO) rather than the traditional gradient descent method.First,principal component analysis(PCA) is used to reduce the dimensions and correlations of input parameters.Second,the PSO-BP is used to optimize the weights and thresholds of the neural networks.Based on the experimental data(0.038 μm polyethersulfone membrane for printing and dyeing wastewater treatment),the simulation is performed with MATLAB.Results show that the PSO-BP neural network has a faster convergence speed and a better agreement with the real data than traditional BP neural network.
【Fund】: 国家科技重大专项资助项目(2009ZX04001-024)
【CateGory Index】: X703;TP183
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