传感技术学报Issue(12)：1643-1648,6.DOI:10.3969/j.issn.1004-1699.2014.12.011
基于模拟退火优化BP神经网络的pH值预测∗
Optimized BP Neural Network Based on Simulated Annealing Algorithm for pH Value Prediction
摘要
Abstract
In order to determine accurate pH value of water automatically,sufficient and typical data of pH value measuring tests are collected as samples,and a pH 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 net-work 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 pH value prediction.关键词
BP神经网络/模拟退火/pH值/非线性回归Key words
BP neural network/simulated annealing/pH value/nonlinear regression分类
信息技术与安全科学引用本文复制引用
尤丽华,吴静静,王瑶,宋淑娟..基于模拟退火优化BP神经网络的pH值预测∗[J].传感技术学报,2014,(12):1643-1648,6.基金项目
国家自然科学基金项目(61305016) （61305016）
江南大学自主科研计划青年基金项目(JUSRP1059) （JUSRP1059）
