Back analysis of geomechanical parameters in underground engineering using artificial bee colony.

Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal al...

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Publicado en:Scientific World Journal pp. 693812 - 693813
Autores principales: Zhu, Changxing, Zhao, Hongbo, Zhao, Ming
Formato: research Journal Article
Publicado: Wiley-Blackwell 2014
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2014
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        atl: Back analysis of geomechanical parameters in underground engineering using artificial bee colony.
      aug:
        au:
          Zhu, Changxing
          Zhao, Hongbo
          Zhao, Ming
        affil: School of Civil Engineering, Henan Polytechnic University, Jiaozuo 454003, China.
      sug:
        subj:
          Algorithms
          Bees and Wasps
          Animal Studies
          Artificial Intelligence
          Models, Biological
      ab: Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal algorithm to search the unknown geomechanical parameters for the problem with analytical solution. To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis. The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution. The results show the proposed method is feasible.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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