基于变权重理论-正态云模型的边坡稳定性研究
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摘要
针对边坡稳定性具有模糊性和随机性的特点,引入云模型理论,建立了基于变权重-正态云理论的边坡稳定性评价模型。以某省际高速公路边坡评估为例,考虑地形地貌、地质环境和气象水文特征等方面因素,选取了10个指标建立综合评价指标体系。首先计算各指标对应评价等级的确定度,采用变权重理论确定指标权重,计算综合确定度,最后根据最大隶属度原则确定边坡稳定性等级。结果表明,待评估边坡稳定性等级分别为不稳定、基本稳定和不稳定,与理想点和神经网络评价模型结果基本一致。
This paper intends to introduce the theory of the cloud model in view of its fuzziness and randomness of the slope stability so as to achieve the reliable measure to appreciate the slope stability in the interprovincial expressway construction. In the given paper,we have also been trying to establish a new evaluation model of the slope stability based on the variable weight theory and the normal cloud theory based on the relevant factors of the topography,the geological environment with the meteorological and hydrological features as a comprehensive evaluation system,including 10 factors concerned,such as those of the height and angle of the slope,the rock quality designation( RQD),the structural features of the rock mass,the ground stress,cohesion,internal friction angle,the maximum daily precipitation,as well as the annual rainstorm periods and the groundwater status-in-situ. In proceeding with research,we have managed to classify the slanting degree of the slope stability into 5 respective levels,that is,the stability level,the sub-stable level,the less stable level,the instable level,and the extremely instable level. At the same time,the digital cloud features can be determined based on the above classification rules. What is more,we have also introduced a normal cloud generator to produce the corresponding cloud models in accordance with the digital cloud features,which can be expected to determine the availability degrees of each index in relation to the each evaluation degree. As to the variable weight theory,it is expected to be used to determine the index weight of each factor. Furthermore,the comprehensive determination degree of the slope stability level can also be worked out on the basis of each index weight and the certainty degree,whereas the slope stability degree can be gained with the maximum membership degree principle. Thus,the final results of our calculation indicate that the stability degrees of the 3 slopes can be taken as the instable level,the less stable level and the stable level,respectively,which have been found generally consistent with the results of the ideal point and neural network evaluation model,as well as in line with the actual investigation results gained on the spot.Thus,the evaluation model of the slope stability we have worked out can be verified feasible and in turn to be adopted to the similar engineering practice as a novel reliable method for slope stability analysis and assessment.
This paper intends to introduce the theory of the cloud model in view of its fuzziness and randomness of the slope stability so as to achieve the reliable measure to appreciate the slope stability in the interprovincial expressway construction. In the given paper,we have also been trying to establish a new evaluation model of the slope stability based on the variable weight theory and the normal cloud theory based on the relevant factors of the topography,the geological environment with the meteorological and hydrological features as a comprehensive evaluation system,including 10 factors concerned,such as those of the height and angle of the slope,the rock quality designation( RQD),the structural features of the rock mass,the ground stress,cohesion,internal friction angle,the maximum daily precipitation,as well as the annual rainstorm periods and the groundwater status-in-situ. In proceeding with research,we have managed to classify the slanting degree of the slope stability into 5 respective levels,that is,the stability level,the sub-stable level,the less stable level,the instable level,and the extremely instable level. At the same time,the digital cloud features can be determined based on the above classification rules. What is more,we have also introduced a normal cloud generator to produce the corresponding cloud models in accordance with the digital cloud features,which can be expected to determine the availability degrees of each index in relation to the each evaluation degree. As to the variable weight theory,it is expected to be used to determine the index weight of each factor. Furthermore,the comprehensive determination degree of the slope stability level can also be worked out on the basis of each index weight and the certainty degree,whereas the slope stability degree can be gained with the maximum membership degree principle. Thus,the final results of our calculation indicate that the stability degrees of the 3 slopes can be taken as the instable level,the less stable level and the stable level,respectively,which have been found generally consistent with the results of the ideal point and neural network evaluation model,as well as in line with the actual investigation results gained on the spot.Thus,the evaluation model of the slope stability we have worked out can be verified feasible and in turn to be adopted to the similar engineering practice as a novel reliable method for slope stability analysis and assessment.
引文
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[14]LI Deqing(李德清),CUI Hongmei(崔红梅),LI Hongxing(李洪兴).Multivariate decision based on hierarchical variable weights[J].Journal of Systems Engineering(系统工程学报),2004,19(3):258-263.
[15]ZHANG Ying(张莹),DAI Jin(代劲),AN Shiquan(安世全).Qualitative evaluation based on cloud model and application in student rating of teaching[J].Computer Engineering and Applications(计算机工程与应用),2012,48(31):210-215.
[2]WU Zhen(武震),LI Wenxiu(李文秀),LEI Zhen(雷振),et al.Stability analysis method for slope of open-pit iron mine[J].Mining and Metallurgical Engineering(矿冶工程),2017,37(1):18-20,24.
[3]PURBA J H.A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment[J].Annals of Nuclear Energy,2014,70:21-29.
[4]WANG Hualan(王花兰),LIANG Yuansheng(梁院生).Performance evaluation model of highway pavement based on extension cloud theory[J].Chinese and Foreign Highway(中外公路),2015,35(3):63-70.
[5]XU Zhengjie(徐征捷),ZHANG Youpeng(张友鹏),SU Hongsheng(苏宏升).Application of risk assessment on fuzzy comprehensive evaluation method based on the cloud model[J].Journal of Safety and Environment(安全与环境学报),2014,14(2):69-72.
[6]ZHAO Feng(赵峰),WANG Kaiming(王开铭),CAO Qian(曹茜).Risk assessment of the traction substation based on the cloud theory and combination weighing method[J].Journal of Safety and Environment(安全与环境学报),2017,17(5):1690-1695.
[7]ZHOU Keping(周科平),LIN Yun(林允),DENG Hongwei(邓红卫),et al.Prediction of rock burst classification using cloud model with entropy weight[J].Transactions of Nonferrous Metals Society of China(中国有色金属学报),2016,26(7):1995-2002.
[8]YUAN Aiping(袁爱平).Stability evaluation of rocky slope based on AHP-normal cloud model[J].Water Resources and Power(水电能源科学),2016,34(9):153-156.
[9]WANG Xinmin(王新民),RONG Shuai(荣帅),ZHAO Maoyang(赵茂阳),et al.Concentration equipment optimization based on variable weight theory and topsis[J].Gold Science and Technology(黄金科学技术),2017,25(3):77-83.
[10]XIE Lüqian(谢榈潜),HOANG Rendong(黄仁东),PENG Huaide(彭怀德).Quality risk evalution for the initial internal supports of the long-lasting shutdown tunnels based on cloud model[J].Joumal of Safety and Environment(安全与环境学报),2018,18(1):45-50.
[11]WANG Peizhuang(汪培庄).Fuzzy sets and random colony shadow(模糊集与随机集落影)[M].Beijing:Beijing Normal University Press,1995:93-102.
[12]LI Hongxing(李洪兴).Factor spaces and mathematical frame of knowledge representation(VIII):variable weight principle[J].Fuzzy Systems and Mathematics(模糊系统与数学),1995,9(3):1-9.
[13]YOU Kesi(游克思),SUN Lu(孙璐),GU Wenjun(顾文钧).Variable weight comprehensive evaluation method in the evaluation of road safety in the mountains[J].Systems Engineering(系统工程),2010,28(5):85-88.
[14]LI Deqing(李德清),CUI Hongmei(崔红梅),LI Hongxing(李洪兴).Multivariate decision based on hierarchical variable weights[J].Journal of Systems Engineering(系统工程学报),2004,19(3):258-263.
[15]ZHANG Ying(张莹),DAI Jin(代劲),AN Shiquan(安世全).Qualitative evaluation based on cloud model and application in student rating of teaching[J].Computer Engineering and Applications(计算机工程与应用),2012,48(31):210-215.