水资源与水工程学报Issue(3)：152-156,5.DOI:10.11705/j.issn.1672-643X.2014.03.31
基于遗传算法的 Elman 神经网络模型在大坝位移预测中的应用
Application of Elman neural network model in prediction of dam deformation based on genetic algorithms
摘要
Abstract
Aimed at the complexity and time variability of forecast of dam deformation ,and the shortage of traditional prediction model ,combined with the overall ability of random search of genetic algorithm and the charactertics of misalignment mapping ,dynamic feedback and memory function of Elman neural net-work, the paper built the model of genetic algorithms ( GA) and Elman neural network .Compared with the Elman neural network ,the GA-Elman model has the characteristics of global convergence and can o-vercome the fault that Elman neural network was susceptible to fail into local minimum .The model was used to forecast some measured data of a dam deformation in a hydropower station .The result showed that the forecast precision of GA-Elman model is high and has practicability in dam deformation prediction .关键词
大坝位移预测/Elman神经网络/遗传算法/GA-Elman模型Key words
dam deformation prediction/Elman neural network/genetic algorithm/GA-Elman model分类
建筑与水利引用本文复制引用
刘雄峰,李博,李俊..基于遗传算法的 Elman 神经网络模型在大坝位移预测中的应用[J].水资源与水工程学报,2014,(3):152-156,5.基金项目
国家自然科学基金项目（41201484）；精密工程与工业测量国家测绘地理信息局重点实验室开放基金项目（PF2011-21）；西北农林科技大学大学生创新性实验计划项目 （）
