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基于KPCA和GA-LSSVR的惠州砖混建筑物震害易损性研究 被引量:3

Study on seismic damage vulnerability of Huizhou brick masonry building based on KPCA and GA-LSSVR model
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摘要 科学地预测城市建筑物震害易损性,以此来分析城市防灾的薄弱环节,是预防及减轻地震损失的关键步骤。惠州建筑物普查结果中,少数抽样建筑物有详细图纸,可以进行具体的震害计算,多数建筑物无详细图纸,尚无合适的精确计算模型。文中对有详细图纸的砖混建筑进行了震害指数计算,根据普查数据表识别并量化了震害影响指标,进而建立了样本库以及基于KPCA和GA_LSSVR的预测模型。在此基础上,对无详细图纸的砖混建筑进行了震害指数预测,得到了惠州区域砖混建筑物的震害易损性矩阵。该预测模型利用KPCA对建筑物震害影响因素进行特征提取,并用LSSVR来对建筑物震害指数进行回归预测,利用GA对LSSVR中的相关参数进行寻优,其可用性和有效性均在文中有所验证。 Scientifically predicting the vulnerability of buildings to analyze the weak links of urban disaster prevention,is the key step to prevent and mitigate the earthquake loss. As Huizhou building survey results,a small number of sampling buildings have detailed drawings,can be carried out specific seismic damage,most buildings without detailed drawings,there is no suitable accurate calculation model. In this paper,the seismic damage index is calculated for the brick building with detailed drawings. The inpact index of seismic damage is identified and quantified according to Huizhou building general survey data. Then the sample datebase and the model of KPCA and GA_LSSVR are established. The model is used to predict the seismic damage index of Huizhou brack masonry building without detailed drawings,and the seismic damage matrix is obtained. This paper uses the KPCA to extract the characteristics of the damage factors,and uses the LSSVR to predict the seismic damage index. The relevant parameters in LSSVR were optimized by GA. This forecasting model's availability and effectiveness are verified in the text.
作者 彭志兰 孙海 高惠瑛 姜慧 PENG ZhilanI;SUN Hai;GAO Huiying;JIANG Hui(College of Engineering, Ocean University of China, Qingdao 266100, China;Guangdong Earthquake Engineering Experimental Center,Guangzhou 510000, China)
出处 《地震工程与工程振动》 CSCD 北大核心 2018年第2期176-183,共8页 Earthquake Engineering and Engineering Dynamics
基金 山东省自然科学基金项目(ZR2016DB25) 青岛市博士后人员应用研究项目 中央高校基本科研业务费~~
关键词 震害预测 震害矩阵 核主成分分析 遗传算法 最小二乘支持向量回归机 seismic damage prediction seismic damage matrix kernel principal component analysis genetic al- gorithm least squares support vector regression
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