摘要
研究了基于遗传规划(GP)理论的大坝变形监测数学模型的建模方法。通过与回归分析模型和BP神经网络模型的拟合精度及预测效果的比较,证明GP模型有更高的拟合精度和更好的预测效果,为大坝变形监测数据处理开辟了一条新的途径。
Based on genetic programming （GP） theory, the mathematical modeling method of dam deformation monitoring is researched. A comparison of the fitting precision and forecasting effect of GP model with that of statistical regression model and BP neural network model indicates that GP model is more precise than the other models. Thus, a new method of data processing for dam deformation monitoring is provided.
出处
《水电自动化与大坝监测》
2007年第5期66-68,共3页
HYDROPOWER AUTOMATION AND DAM MONITORING
关键词
大坝变形监测
数学模型
遗传规划
回归分析
神经网络
dam deformation monitoring
mathematical model
genetic programming （GP）
regression analysis
neural network
