红水河2024，Vol.43Issue(2)：1-5,5.DOI:10.3969/j.issn.1001-408X.2024.02.001
基于FOA-BP-AdaBoost的大坝变形预测模型及应用
Dam Deformation Prediction Model Based on FOA-BP-AdaBoost and Its Application
摘要
Abstract
In order to improve the prediction accuracy of dam deformation monitoring and solve the problem that the deformation is affected by many factors,the AdaBoost strong prediction combination model based on fruit fly optimization algorithm(FOA)and BP neural network(FOA-BP-AdaBoost)is proposed,and compared with the prediction accuracy of BP neural network model and FOA-BP neural network model applied to engineering examples.The results show that the strong prediction model integrates the characteristics of global optimization of fruit fly algorithm,local optimization of BP neural network and AdaBoost"optimal selection",and optimizes the prediction effect to the greatest extent;The application of the example confirms the accuracy and effectiveness of the FOA-BP-AdaBoost model in the field of dam deformation prediction.The model has been successfully applied to engineering examples,which can provide reference for similar projects.关键词
大坝/变形监测/FOA-BP-AdaBoost模型/强预测模型/果蝇优化算法/BP神经网络Key words
dam/deformation monitoring/FOA-BP-AdaBoost model/strong prediction model/fruit fly optimization algorithm/BP neural network分类
建筑与水利引用本文复制引用
王凯,李鸳承,范亚军,何广焕,蒙金龙,赵磊..基于FOA-BP-AdaBoost的大坝变形预测模型及应用[J].红水河,2024,43(2):1-5,5.基金项目
广西高校中青年教师科研基础能力提升项目(2020KY35022) （2020KY35022）
