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Chinese Journal of Underground Space and Engineering. 2022, (S2) Core

Prediction of Rockburst Intensity Based on PCA-SOFM ModelChinese Full TextEnglish Full Text (MT)

Chen Zehuang;Li Kegang;Li Mingliang;Qin Qingci;Mao Mingfa;School of Land and Resources Engineering, Kunming University of Science and Technology;Yunnan Key Laboratory of Sino-German Blue Mining and Utilization of Special Underground Space;Yunnan Chihong Zn＆Ge, Co., Ltd.;

Abstract: Rockburst is affected by many conditional factors, requiring the integrity of rockburst prediction index system. Prediction index system of rockburst intensity grade is constructed by selecting the elastic deformation energy index Wet, stress coefficient σθ/σc, brittleness coefficient σc/σt, uniaxial compressive strength σc, uniaxial tension σt, and tangential stress of surrounding rock σθ. PCA method is used... More
Keywords：

rock mechanics; principle component analysis（PCA）; self-organizing feature mapping neural network; prediction of rockburst intensity grade; Euclidean distance;

  • Series：

    (C) Architecture/ Energy/ Traffic/ Electromechanics, etc; (A) Mathematics/ Physics/ Mechanics/ Astronomy

  • Subject：

    Geology; Architecture and Engineering

  • Classification Code：

    TU45

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