{"title":"基于进化神经网络的深基坑支护结构位移反分析","authors":"Shengli Zhao, Yan Liu","doi":"10.1109/ICWAPR.2009.5207405","DOIUrl":null,"url":null,"abstract":"An evolutionary neural network method of displacement back analysis on supporting structure of deep foundation pit is proposed to search the optimal mechanical parameters. First, the BP network replaces the time-consuming finite element method to establish the non-linear relationship between the values of deep foundation pit mechanical parameters and displacement of its supporting structure, then genetic algorithm is used as an optimization method to search the optimal mechanical parameters in their global ranges. Application of this methodology is illustrated with a numerical example and reasonable results are yielded.","PeriodicalId":424264,"journal":{"name":"2009 International Conference on Wavelet Analysis and Pattern Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Displacement back analysis on supporting structure of deep foundation pit based on evolutionary neural nrtwork\",\"authors\":\"Shengli Zhao, Yan Liu\",\"doi\":\"10.1109/ICWAPR.2009.5207405\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An evolutionary neural network method of displacement back analysis on supporting structure of deep foundation pit is proposed to search the optimal mechanical parameters. First, the BP network replaces the time-consuming finite element method to establish the non-linear relationship between the values of deep foundation pit mechanical parameters and displacement of its supporting structure, then genetic algorithm is used as an optimization method to search the optimal mechanical parameters in their global ranges. Application of this methodology is illustrated with a numerical example and reasonable results are yielded.\",\"PeriodicalId\":424264,\"journal\":{\"name\":\"2009 International Conference on Wavelet Analysis and Pattern Recognition\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Wavelet Analysis and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWAPR.2009.5207405\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2009.5207405","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Displacement back analysis on supporting structure of deep foundation pit based on evolutionary neural nrtwork
An evolutionary neural network method of displacement back analysis on supporting structure of deep foundation pit is proposed to search the optimal mechanical parameters. First, the BP network replaces the time-consuming finite element method to establish the non-linear relationship between the values of deep foundation pit mechanical parameters and displacement of its supporting structure, then genetic algorithm is used as an optimization method to search the optimal mechanical parameters in their global ranges. Application of this methodology is illustrated with a numerical example and reasonable results are yielded.