| 基于果蝇优化算法的GRNN模型在边坡稳定预测中的应用 |
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| 引用本文： | 王海军,涂凯,闫晓荣.基于果蝇优化算法的GRNN模型在边坡稳定预测中的应用[J].水电能源科学,2015,33(1):124-126. |
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| 作者姓名： | 王海军 涂凯 闫晓荣 |
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| 作者单位： | 天津大学 水利工程仿真与安全国家重点实验室， 天津 300072,天津大学 水利工程仿真与安全国家重点实验室， 天津 300072,中国民航大学 机场学院， 天津 300300 |
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| 基金项目： | 国家自然科学基金青年基金项目(50909072)；中央高校基本科研项目（3122014C012）；国家自然科学基金创新研究群体科学基金项目（51321065） |
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| 摘 要： | 鉴于边坡系统是一个复杂的多因素影响的非线性系统,综合考虑边坡的物理状态和环境因素,采用了一种基于果蝇优化算法(FOA)的广义回归神经网络(GRNN)模型(FOAGRNN)预测边坡的稳定状态,并与BP神经网络预测模型结果进行比较。结果表明,FOAGRNN预测的精度较高,基本反映了边坡稳定的真实状态。
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| 关 键 词： | 边坡稳定 果蝇优化算法 广义回归神经网络 预测 |
Application of General Regression Neural Network to Predict Slope Stability Based on Fruit Fly Optimization Algorithm |
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| WANG Hai-jun,TU Kai and YAN Xiao-rong.Application of General Regression Neural Network to Predict Slope Stability Based on Fruit Fly Optimization Algorithm[J].International Journal Hydroelectric Energy,2015,33(1):124-126. |
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| Authors: | WANG Hai-jun TU Kai and YAN Xiao-rong |
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| Affiliation: | State Key Laboratory of Water Conservancy Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China,State Key Laboratory of Water Conservancy Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China and Airport College, Civil Aviation University of China, Tianjin 300300, China |
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| Abstract: | A slope system is a complicated nonlinear system which is affected by lots of factors. General regression neural network method improved by fruit fly optimization algorithm (FOAGRNN) is used to predict slope stability by comprehensively considering physical status of slope and environmental factor. Compared with BP neural network method, the results show that the FOAGRNN has higher prediction accuracy, which basically reflects the true state of slope stability. |
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| Keywords: | slope stability fruit fly optimization algorithm general regression neural network prediction |
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