基于权重反分析和标准化模糊综合评价的岩爆预测模型

doi:10.13722/j.cnki.jrme.2014.10.024

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (555 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要针对岩爆预测问题，选取应力系数?θ/?c、脆性系数?c/?t、弹性能量指数Wet作为评价指标，选择2种分级标准对岩爆指标进行标准化处理，选用正态分布函数构建隶属度函数，以Matlab编程反分析指标权重，建立基于权重反分析的标准化模糊综合评价模型。该模型解决了传统模型存在的权重主观性过大，隶属度函数不符合实际的问题，理论上更完备。选择国内外46组岩爆数据作为样本反分析权重，以3个工程实例对比不同分级标准和权重的应用效果，结果显示基于反分析权重的预测模型比基于主观权重的预测模型效果更优，不同分级标准所得结果并不一致，还需进一步对比分析。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章

关键词 ：岩石力学, 岩爆, 预测, 权重, 反分析, 模糊综合评价, 标准化

Abstract：The stress coefficient ?θ/?c，the brittleness coefficient ?c/?t and the elastic energy index Wet were selected as the evaluation indices，and two classification criteria were chosen for normalization of the rockburst indices. A normal distribution function was selected to construct the membership functions. MATLAB programming was adopted for the back analysis of index weights. A standardized fuzzy comprehensive evaluation model based on the weighted back analysis was established. The model is theoretically sounder and solves the problems of over subjectivity of weights and the unrealistic membership functions existed in the traditional models. 46 sets of rockburst data at home and abroad were selected as the samples for weighted back analysis，and three engineering cases were used to compare the effects of application of different classification criteria and weights. Results show that the prediction model based on back analysis weights is better than the one based on subjective weights. Results from applying different classification criteria are inconsistent with each other，so that further investigation is required.

Key words： rock mechanics rockburst prediction weight back analysis fuzzy comprehensive evaluation standardization

收稿日期: 2014-01-26

引用本文:

陈鹏宇，余宏明，师华鹏. 基于权重反分析和标准化模糊综合评价的岩爆预测模型[J]. 岩石力学与工程学报, 2014, 33(10): 2154-2160.
CHEN Pengyu，YU Hongming，SHI Huapeng. PREDICTION MODEL FOR ROCKBURST BASED ON WEIGHTED BACK ANALYSIS AND STANDARDIZED FUZZY COMPREHENSIVE EVALUATION. , 2014, 33(10): 2154-2160.

链接本文:

http://www.rockmech.org/CN/10.13722/j.cnki.jrme.2014.10.024 或 http://www.rockmech.org/CN/Y2014/V33/I10/2154

[6]	LI H. Pattern recognition and prediction study of rock burst based on neural network[J]. Journal of Coal Science and Engineering(China)，2010，16(4)：347-351. " target="_blank">
[8]	DONG L J，LI X B，PENG K. Prediction of rockburst classification using Random Forest[J]. Transactions of Nonferrous Metals Society of China，2013，23(2)：472-477.
[9]	宫凤强，李夕兵. 岩爆发生和烈度分级预测的距离判别方法及应用[J]. 岩石力学与工程学报，2007，26(5)：1 012-1 018.(GONG Fengqiang，LI Xibing. A distance discriminant analysis method for prediction of possibility and classification of rockburst and its application[J]. Chinese Journal of Rock Mechanics and Engineering，2007，26(5)：1 012-1 018.(in Chinese)) " target="_blank">
[13]	SHAO C Y. The implication of fuzzy comprehensive evaluation method in evaluating internal financial control of enterprise[J]. International Business Research(IBR)，2009，2(1)：210-214. " target="_blank">
[16]	李芬，孟刚. 模糊综合评判法在围岩稳定性分类中的应用[J]. 武汉大学学报：工学版，2011，44(6)：744-747.(LI Fen，MENG Gang. Application of fuzzy synthesis assessment method to classification of surrounding rock stability[J]. Engineering Journal of Wuhan University，2011，44(6)：744-747.(in Chinese)) " target="_blank">
[11]	LIU Z B，SHAO J F，XU W Y，et al. Prediction of rock burst classification using the technique of cloud models with attribution weight[J]. Natural Hazards，2013，68(2)：549-568.
[15]	王元汉，李卧东，李启光，等. 岩爆预测的模糊数学综合评判方法[J]. 岩石力学与工程学报，1998，17(5)：493-501.(WANG Yuanhan，LI Wodong，LEE P K，et al. Method of fuzzy comprehensive evaluations for rockburst prediction[J]. Chinese Journal of Rock Mechanics and Engineering，1998，17(5)：493-501. (in Chinese))
[18]	居培，翟应虎. 基于正态分布理论的模糊综合评判法识别岩性[J]. 科学技术与工程，2012，12(21)：5 253-5 256.(JU Pei，ZHAI Yinghu. Lithology identification analysis based on normal distribution theory and fuzzy synthetic evaluation method[J]. Science Technology and Engineering，2012，12(21)：5 253-5 256.(in Chinese)) " target="_blank">
[20]	贾义鹏，吕庆，尚岳全. 基于粒子群算法和广义回归神经网络的岩爆预测[J]. 岩石力学与工程学报，2013，32(2)：343-348.(JIA Yipeng，LU Qing，SHANG Yuequan. Rockburst prediction using particle swarm optimization algorithm and general regression neural network[J]. Chinese Journal of Rock Mechanics and Engineering，2013，32(2)：343-348.(in Chinese))
[1]	冯夏庭，陈炳瑞，张传庆，等. 岩爆孕育过程的机制、预警与动态调控[M]. 北京：科学出版社，2013：1-3.(FENG Xiating，CHEN Bingrui，ZHANG Chuanqing，et al. Mechanism，warning and dynamic control of rockburst development processes[M]. Beijing：Science Press，2013：1-3.(in Chinese)) " target="_blank">
[5]	HOEK E，BROWN E T. Underground excavation in rock[M]. London：The Institute of Mining and Metallurgy，1980：367-381. " target="_blank">
[19]	邱道宏，张乐文，李术才，等. 基于优化理论的权重反分析方法研究[J]. 岩土工程学报，2010，32(2)：259-264.(QIU Daohong，ZHANG Lewen，LI Shucai，et al. Weight back analysis method based on optimization theory[J]. Chinese Journal of Geotechnical Engineering，2010，32(2)：259-264.(in Chinese)) " target="_blank">
[3]	RUSSNES B F. Analyses of rockburst in tunnels in valley sides[M. S. Thesis][D]. Trondheim：Norwegian Institute of Technology，1994. " target="_blank">
[7]	ZHOU J，LI X B，SHI X Z. Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines[J]. Safety Science，2012，50(4)：629-644. " target="_blank">
[2]	DURRHEIM R J，HAILE A，ROBERTS M K C，et al. Violent failure of a remnant in a deep South African gold mine[J]. Tectonophysics，1998，289(1)：105-116. " target="_blank">
[4]	TURCHANINOV I A，MARKOV G A，GZOVSKY M V，et al. State of stress in the upper part of the earth's crust based on direct measurements in mines and on tectonophysical and seismological studies[J]. Physics of the Earth and Planetary Interiors，1972，6(4)：229-234. " target="_blank">
[10]	AMOUSSOU C A，CANDAN G，LI W，et al. Knowledge-based and data-driven fuzzy modeling for rockburst prediction[J]. International Journal of Rock Mechanics and Mining Sciences，2013，61：86-95. " target="_blank">
[12]	胡建华，尚俊龙，周科平. 岩爆烈度预测的改进物元可拓模型与实例分析[J]. 中国有色金属学报，2013，23(2)：495-502.(HU Jianhua，SHANG Junlong，ZHOU Keping. Improved matter-element extension model and its application to prediction of rockburst intensity[J]. Chinese Journal of Nonferrous Metals，2013，23(2)：495-502.(in Chinese)) " target="_blank">
[14]	张国权. 金山店铁矿采矿巷道围岩稳定性模糊综合评价[硕士学位论文][D]. 武汉：武汉科技大学，2012.(ZHANG Guoquan. Fuzzy- synthetical evaluation on stability of rock roadway in Jinshan store[M. S. Thesis][D]. Wuhan：Wuhan University of Science and Technology，2012.(in Chinese)) " target="_blank">
[17]	丁向东，吴继敏. 岩体质量模糊分类方法[J]. 水利水电科技进展，2006，26(3)：18-20.(DING Xiangdong，WU Jimin. Fuzzy classification of rock mass[J]. Advances in Science and Technology of Water Resource，2006，26(3)：18-20.(in Chinese)) " target="_blank">