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《Chinese Journal of Sensors and Actuators》 2014-12
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Optimized BP Neural Network Based on Simulated Annealing Algorithm for pH Value Prediction

YOU Lihua;WU Jingjing;WANG Yao;SONG Shujuan;School of Mechanical Engineering,Jiangnan University;Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology;  
In order to determine accurate p H value of water automatically,sufficient and typical data of p H value measuring tests are collected as samples,and a p H value prediction method of optimized BP neural network based on simulated annealing algorithm is presented. The simulated annealing algorithm is employed to optimize the weights and thresholds of BP neural network,and selection methods of the training samples and the number of the hidden layer nodes are improved,thus yield an optimal solution of BP neural network. The obtained BP neural network is tested by samples,and the prediction results are compared with ones given by a nonlinear regression method.Experimental results exhibit that the proposed method provides better fitting ability and higher accuracy for p H value prediction.
【Fund】: 国家自然科学基金项目(61305016);; 江南大学自主科研计划青年基金项目(JUSRP1059)
【CateGory Index】: TP183;TP274
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