大坝观测数据的模糊神经网络分析  

FUZZY NEURAL NETWORK ANALYSIS OF OBSERVATION DATA OF DAMS

作　　者：徐洪钟[1] 单泰松[2] 吴中如[1] 

机构地区：[1]河海大学水利水电学院,南京210098 [2]南京大学,南京210093

出　　处：《大坝观测与土工测试》2001年第3期16-17,22,共3页Dam Observation and Geotechnical Tests

摘　　要：针对某一混凝土重力坝水平位移实测值建立模糊神经网络预报模型，用改进的这传算法对参数进行调整和优化，并用自组织竞争神经网络来优化换糊神经网络结构。计算结果表明，其预报精度优于常规的统计回归模型。Based on the observation data of a the horizontal displacement of a gravity dam. a fuzzy neural network model is presented in this paper. The improved genetic algorithm is used to modify and optimize the parameter, and the self-organization competition neural network is applied to optimize the structure of the fuzzy neural network. The result shows that the prediction is more precise than that of the regression model.

关 键 词：大坝 模糊神经网络 遗传算法 数据观测 

分 类 号：TV698.1[水利工程—水利水电工程]