基于改进遗传算法优化BP神经网络的单体建筑物震害评估方法  

A Single Building Seismic Damage Assessment Method Based on Improved Genetic Algorithm Optimized BP Neural Network

作　　者：孟雅湉 熊永良 郭红梅[2] 张莹[2] 赵真 江雪梨 Meng Yatian;Xiong Yongliang;Guo Hongmei;Zhang Ying;Zhao Zhen;Jiang Xueli(Faculty of Geosciences and Environmental Engineering,Southwest Jiaotong University,Chengdu 611756,China;Sichuan Earthquake Agency,Chengdu 610041,China)

机构地区：[1]西南交通大学,地球科学与环境工程学院,成都611756 [2]四川省地震局,成都610041

出　　处：《中国地震》2023年第4期785-794,共10页Earthquake Research in China

基　　金：“十三五”国家重点研发计划课题(2020YFA0710603);四川地震科技创新团队专项(201901)共同资助。

摘　　要：结合机器学习算法最新研究进展,提出一种基于改进遗传算法优化BP神经网络的单体建筑物震害评估方法。以四川地区为例,通过改进遗传算法优化BP神经网络建立评估模型,输出评估区域内不同结构类型单体建筑物在各震害影响因素综合作用下的破坏等级,并通过实际算例分析对模型的有效性进行验证。结果表明,该方法可快速、准确地评估单体建筑物震害情况。This paper proposes a single building damage assessment method based on improved genetic algorithm optimized back propagation(BP)neural network,after reviewing the latest research progress in machine learning algorithms.Taking the Sichuan area as an example,the improved genetic algorithm optimized BP neural network is used to establish an assessment model and to output the damage levels of single buildings with different structural types in the assessment area under the combined effect of various seismic damage influencing factors.The validity of the model is verified through the analysis of practical examples,and the results show that the method can quickly and accurately assess the seismic damage of single buildings.

关 键 词：单体建筑物 震害评估 遗传算法 BP神经网络 

分 类 号：P315[天文地球—地震学]