基于最优组合权重的GRA-TOPSIS深井巷道支护方案优选
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摘要
为确定矿山最佳深井巷道支护方案,基于最优组合权重构建深井巷道支护GRATOPSIS综合评价模型,以某深井矿山为例,选取14项评价指标作为GRA-TOPSIS综合评价模型的判别指标,运用层次分析法(AHP)和熵权法确定组合权重,引入最小鉴别信息原理优化组合赋权,利用GRA-TOPSIS综合评价方法定量分析备选支护方案,基于评价指标的综合优越度确定最优巷道支护方案。结果表明,5种备选支护方案的综合优越度分别为:50.4%,49.0%,56.6%,42.7%,55.8%。顶板与两帮均锚杆锚索、喷射混凝土,底板锚索并注浆联合支护方式为最优决策。该评价模型能够对支护方案定量评价,模型鲁棒性强。
In order to determine the best support scheme for deep well roadway in the mine,the GRATOPSIS comprehensive evaluation model of deep roadway support was constructed based on the optimal combination weight.With a deep mine as an example,14 evaluation indicators were selected as the discriminative indicators of the GRA-TOPSIS comprehensive evaluation model.The analytic hierarchy process(AHP)and entropy weight method were used to determine the combined weights,and the principle of minimum discriminant information was introduced to optimize the combination weighting.The GRA-TOPSIS comprehensive evaluation method was used to quantitatively analyze the comprehensive superiority of the alternative support scheme based on the evaluation index to determine the optimal roadway support scheme.The results showed that the comprehensive superiority of the five alternative support schemes were:50.4%,49.0%,56.6%,42.7%,55.8%respectively,and the combined support with anchor bolt anchor rope used on the roof and both sides,shotcrete,floor anchor rope and grouting was the optimal scheme.In conclusion,the evaluation model proposed can quantitatively evaluate the support scheme with its robustness.
In order to determine the best support scheme for deep well roadway in the mine,the GRATOPSIS comprehensive evaluation model of deep roadway support was constructed based on the optimal combination weight.With a deep mine as an example,14 evaluation indicators were selected as the discriminative indicators of the GRA-TOPSIS comprehensive evaluation model.The analytic hierarchy process(AHP)and entropy weight method were used to determine the combined weights,and the principle of minimum discriminant information was introduced to optimize the combination weighting.The GRA-TOPSIS comprehensive evaluation method was used to quantitatively analyze the comprehensive superiority of the alternative support scheme based on the evaluation index to determine the optimal roadway support scheme.The results showed that the comprehensive superiority of the five alternative support schemes were:50.4%,49.0%,56.6%,42.7%,55.8%respectively,and the combined support with anchor bolt anchor rope used on the roof and both sides,shotcrete,floor anchor rope and grouting was the optimal scheme.In conclusion,the evaluation model proposed can quantitatively evaluate the support scheme with its robustness.
引文
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[17]朱雪龙.应用信息论基础[M].北京:清华大学出版社,2001:257-258.ZHU Xuelong.Application of information theory[M].Beijing:Tsinghua University Press,2001:257-258.(in Chinese)
[18]向洁,邱泽晶.基于TOPSIS法和灰色关联度的节能技术优选决策[J].节能技术,2017,35(2):142-146,176.XIANG Jie,QIU Zejing.Optimal decision of energy-saving technologies based on TOPSIS method and grey relational degree[J].Energy Conservation Technology,2017,35(2):142-146,176.(in Chinese)
[19]王新民,王石,鄢德波,等.基于未确知测度理论的充填管道堵塞风险性评价[J].中国安全科学学报,2012,22(4):151-156.WANG Xinmin,WANG Shi,YAN Debo,et al.Risk assessment on blocking of filling pipeline based on uncertainty measurement theory[J].China Safety Science Journal,2012,22(4):151-156.(in Chinese)
[20]张钦礼,肖崇春,陈秋松,等.某矿山最佳充填站站址方案选择[J].科技导报,2013,31(19):39-43.ZHANG Qinli,XIAO Chongchun,CHEN Qiusong,et al.Best selective scheme for the filling station location of a certain mine[J].Science&Technology Review,2013,31(19):39-43.(in Chinese)
[2]郑海力.基于多级模糊评判与嵌套式粗糙集理论的深井巷道支护方案优选体系[J].化工矿物与加工,2012,41(2):23-27.ZHENG Haili.Optimization system for the deep roadway support schemes based on multi-stage fuzzy and nested rough sets theory[J].Industrial Minerals and Processing,2012,41(2):23-27.(in Chinese)
[3]Niedbalski Z,Majcherczyk T.Indicative assessment of design efficiency of mining roadways[J].Journal of Sustainable Mining,2018,17(3):131-138.
[4]Mahdevari S,Shahriar K,Sharifzadeh M,et al.Stability prediction of gate roadways in longwall mining using artificial neural networks[J].Neural Computing and Applications,2017,28(11):3537-3555.
[5]Farzi M,Pakbaz M S,Aminpour H A.Selection of support system for urban deep excavations:A case study in Ahvaz geology[J].Case Studies in Construction Materials,2018,8:131-138.
[6]王望珍,陈翼飞,李素芹,等.基于博弈论和相对熵的基坑支护方案优选[J].数学的实践与认识,2015,45(6):165-171.WANG Wangzhen,CHEN Yifei,LI Suqin,et al.Optimization of supporting schemes for foundation pit based on game theory and relative entropy evaluation method[J].Mathematics in Practice and Theory,2015,45(6):165-171.(in Chinese)
[7]Wang H W,Jiang Y D,Xue S,et al.Influence of fault slip on mining-induced pressure and optimization of roadway support design in fault-influenced zone[J].Journal of Rock Mechanics and Geotechnical Engineering,2016,8(5):660-671.
[8]Cao R H,Cao P,Lin H.Support technology of deep roadway under high stress and its application[J].International Journal of Mining Science and Technology,2016,26(5):787-793.
[9]李必红,周健,史秀志.深基坑支护结构选型决策的Fisher判别分析模型[J].重庆大学学报,2011,34(9):109-116.LI Bihong,ZHOU Jian,SHI Xiuzhi.Fisher discriminant analysis model for selecting the retaining structure type of deep foundation pit[J].Journal of Chongqing University,2011,34(9):109-116.(in Chinese)
[10]贺永俊,李超.基于主成分分析与BP神经网络的深基坑支护方案优选[J].四川建筑科学研究,2015,41(4):32-35,39.HE Yongjun,LI Chao.Optimization of supporting plan for deep foundation pit based on principal component analysis and BP neural network[J].Sichuan Building Science,2015,41(4):32-35,39.(in Chinese)
[11]王宏伟,武旭,陈瀚,等.神经网络在支护优选及变形预测中的应用[J].矿业研究与开发,2016,36(6):25-29.WANG Hongwei,WU Xu,CHEN Han,et al.Application of neural network in optimal selection of support patterns and deformation prediction[J].Mining Research and Development,2016,36(6):25-29.(in Chinese)
[12]陈建宏,郑海力,刘振肖,等.基于优势关系的粗糙集的巷道支护方案评价体系[J].中南大学学报(自然科学版),2011,42(6):1698-1703.CHEN Jianhong,ZHENG Haili,LIU Zhenxiao,et al.Rough sets of laneway supporting schemes evaluation system based on dominance relation[J].Journal of Central South University(Science and Technology),2011,42(6):1698-1703.(in Chinese)
[13]唐诗卉.基于未确知理论的巷道支护方案评价体系及应用[J].科技导报,2014,32(17):29-34.TANG Shihui.An unascertained theory based evaluation system for roadway support schemes and its application[J].Science&Technology Review,2014,32(17):29-34.(in Chinese)
[14]周伟,肖莉明,黄广全,等.粗糙集指标简约的装配设计方案模糊评价[J].重庆大学学报,2018,41(6):24-34.ZHOU Wei,XIAO Liming,HUANG Guangquan,et al.Fuzzy evaluation of assembly design scheme based on attribute value reduction of rough sets[J].Journal of Chongqing University,2018,41(6):24-34.(in Chinese)
[15]张钦礼,程健,王新民,等.基于灰色关联和加权TOPSIS法的采矿方法优选[J].科技导报,2013,31(31):38-42.ZHANG Qinli,CHENG Jian,WANG Xinmin,et al.Mining method optimization based on GRA and weighted TOPSISmethod[J].Science&Technology Review,2013,31(31):38-42.(in Chinese)
[16]薛希龙,王新民,张钦礼,等.充填管道磨损风险评估的组合权重与可变模糊耦合模型[J].中南大学学报(自然科学版),2016,47(11):3752-3758.XUE Xilong,WANG Xinmin,ZHANG Qinli,et al.An integrated model of combination weights and variable fuzzy on evaluating backfill pipeline wear risk[J].Journal of Central South University(Science and Technology),2016,47(11):3752-3758.(in Chinese)
[17]朱雪龙.应用信息论基础[M].北京:清华大学出版社,2001:257-258.ZHU Xuelong.Application of information theory[M].Beijing:Tsinghua University Press,2001:257-258.(in Chinese)
[18]向洁,邱泽晶.基于TOPSIS法和灰色关联度的节能技术优选决策[J].节能技术,2017,35(2):142-146,176.XIANG Jie,QIU Zejing.Optimal decision of energy-saving technologies based on TOPSIS method and grey relational degree[J].Energy Conservation Technology,2017,35(2):142-146,176.(in Chinese)
[19]王新民,王石,鄢德波,等.基于未确知测度理论的充填管道堵塞风险性评价[J].中国安全科学学报,2012,22(4):151-156.WANG Xinmin,WANG Shi,YAN Debo,et al.Risk assessment on blocking of filling pipeline based on uncertainty measurement theory[J].China Safety Science Journal,2012,22(4):151-156.(in Chinese)
[20]张钦礼,肖崇春,陈秋松,等.某矿山最佳充填站站址方案选择[J].科技导报,2013,31(19):39-43.ZHANG Qinli,XIAO Chongchun,CHEN Qiusong,et al.Best selective scheme for the filling station location of a certain mine[J].Science&Technology Review,2013,31(19):39-43.(in Chinese)
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