基于AJSO-NOGM(1,1)组合模型某抽水蓄能电站库岸边坡变形预测  

Prediction of Reservoir Bank Slope Deformation of a Pumped Storage Power Station Based on AJSO⁃NOGM(1,1)Combined Model

作　　者：陈国锋 李广凯 马仿校 赵云飞 CHEN Guofeng;LI Guangkai;MA Fangxiao;ZHAO Yunfei(Zhejiang Huadong Surveying and Engineering Safety Technology Co.,Ltd.,Hangzhou 310014,China;North China Development and Construction Branch,State Grid Xinyuan Holdings Co.,Ltd.,Tianjin 300202,China;Linyi Public Security Bureau,Linyi 276000,China)

机构地区：[1]浙江华东测绘与工程安全技术有限公司,浙江杭州310014 [2]国网新源控股有限公司华北开发建设分公司,天津300202 [3]临沂市公安局,山东临沂276000

出　　处：《人民黄河》2024年第12期149-154,共6页Yellow River

摘　　要：水库边坡变形演变表现出明显的时效特性,基于灰色系统新信息优先理论,通过引入基于新型初始条件优化的等间距NOGM(1,1)模型来强化最新时效因素对水库边坡变形趋势的影响和修正作用,从而提高最新环境变量对边坡变形的影响比重,并采用人工水母搜索算法(Artificial Jellyfish Search Optimizer, AJSO)对相关模型参数进行智能寻优,构建了用于水库边坡变形预测的AJSO-NOGM(1,1)模型。算例分析表明,本文方法相比传统灰色系统GM(1,1)模型预测值与实测值具有更高的相关系数,并且均方根误差和平均绝对系数均优于传统GM(1,1)模型的,可以显著提高边坡变形预测精度和鲁棒性,较好地反映水库岩石边坡变形趋势。The deformation evolution of reservoir slope shows obvious time⁃sensitive characteristics.Based on the gray system new information priority theory,this paper introduced an equidistant NOGM(1,1)model based on new initial condition optimization to strengthen the latest time⁃sensitive factors on reservoir slope,thus,the influence proportion of the latest environmental variables on slope deformation was in⁃creased.It used the artificial jellyfish search algorithm to intelligently optimize the relevant model parameters and build the AJSO⁃NOGM(1,1)model for reservoir slope deformation prediction.The example analysis shows that the method has higher prediction accuracy and well re⁃flects the deformation trend of reservoir slope compared with the traditional gray system GM(1,1)model.

关 键 词：边坡变形 预测 NOGM(1 1) AJSO 水库 抽水蓄能电站 

分 类 号：TV223[水利工程—水工结构工程]