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文章基本信息

  • 标题:Combined Forecasting Mode of Subgrade Settlement Based on Support Vector Machine and Real-coded quantum Evolutionary Algorithm
  • 本地全文:下载
  • 作者:Gao Hui ; Huang Jun
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2015
  • 卷号:8
  • 期号:11
  • 页码:315-322
  • DOI:10.14257/ijhit.2015.8.11.27
  • 出版社:SERSC
  • 摘要:Due to the normal forecasting methods for subgrade settlement using observation data have different applicability and disadvantages, The Combined forecasting model is put forward based on support vector machine (SVM) and real-coded quantum evolutionary algorithm (RQEA) in this paper. Its core is that, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve which has S-type characteristic are chosen as single forecasting model, then support vector machine is used to combine the predicting results of each single forecasting model, at the same time, RQEA is adopted to optimize support vector machine parameter to improve the SVM's performance. The analytical result of engineering practice indicates that the proposed combined forecasting model of subgrade settlement base on SVM and RQEA can not only improve the predicting accuracy, but also reduce the predicting risk, and can meet engineering demand.
  • 关键词:Subgrade Settlement prediction; Combination forecast model; Support ; vector machine; Real-coded quantum evolutionary algorithm
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