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ID:36807405
大小:4.89 MB
页数:62页
时间:2019-05-15
《神东矿区开采沉陷主控因素及GA-WNN下沉系数预计模型研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、论文题目:神东矿区开采沉陷主控因素及GA-WNN下沉系数预计模型研究专业:环境科学硕士生:肖良(签名)指导教师:夏玉成(签名)摘要基于神东矿区具体地质条件,通过理论分析、借助计算机数值模拟、科学计算方法,研究神东矿区开采沉陷的主控因素,将其引入到下沉系数的预计当中,推导出在一定开采条件下沙基比、松散层厚度等地质因素与采煤沉陷下沉系数的预计关系式,并提出开采沉陷下沉系数的GA-WNN(遗传小波神经网络)预计模型。根据神东矿区煤层赋存特点,借助模糊层次分析可知,神东矿区开采沉陷的主控因素为:沙基比、松散层厚度、采厚、
2、关键层的类型及位置、覆岩综合硬度,其影响权重分别为:0.2211、0.1538、0.1489、0.1138、0.0861。在神东矿区达到充分采动的情况下,若不考虑采矿因素,覆岩综合硬度与开采沉陷下沉系数成反比关系;沙基比、松散层厚度与开采沉陷下沉系数成正比关系。在覆岩综合硬度较难计算的情况下,可利用沙基比λ、松散层厚度χ对开采沉陷下沉系数η进行预计,预计公式如下:−2η=0.3645318+1.687368λ−2.733013×10χ利用遗传算法(GA——GeneticAlgorithm)优化小波(W——Wave
3、let)神经网络(NN——NeuralNetwork),建立开采沉陷下沉系数预计模型GA-WNN,其预计结果与实际观测值基本符合,精度较高,适用于神东矿区开采沉陷下沉系数的预计。关键词:开采沉陷;主控因素;数值模拟;预计公式;遗传算法研究类型:基础研究Subject:StudyonMainControllingFactorsandPredictionModelsBaseonGA-WNNofMiningSubsidenceCoefficientSpecialty:EnviormentalScienceName:Xi
4、aoLiang(Signature)Instructor:XiaYu-cheng(Signature)ABSTRACTAccordingtogologicalconditionsofShendongminingarea,themaincontrollingfactorsofminingsubsidenceareselectedandintroducedintothemodelsofminingsubsidencepredictionbymeansoftheoreticalanalysis,numericalsim
5、ulationsandscientificprograms.Andtherelationbetweensubsidencecoefficientandthemaincontrollingfactorsarederived;theOptimizedWaveletNeuralNetworkbasedonGeneticAlgorithm(GA-WNN)isappliedtothepredictionofminingsubsidence.Usingimprovedfuzzyanalyticalhierarchyproce
6、ss,themaster-factorsofminingsubsidenceareselectedastheratioandthicknessoflossesbed,miningthick,comprehensivehardnessofcoverrocks,thepositionandtypeofkeystratum,eachofwhoseweightare0.2211、0.1538、0.1489、0.1138、0.0861.Underthefullminnigofthesameintensity,subside
7、ncecoefficientisinverselyproportionaltocomprehensivehardnessofcoverrocks,andproportionaltotheratioandthicknessoflossesbed.Whenthecomprehensivehardnessofcoverrocksisdifficulttoηχdetermine,thesubsidencecoefficient()ispredictedusingtheratio(λ)andthickness()oflos
8、sesbed,theregressionequationisasfollowes:−2η=.03645318+.1687368λ−.2733013×10χBasedonGA-WNNandnumericalsimulations,theothermodelofminingsubsidencepredictionisconducted.Thepracticalsimulati
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