中国安全生产科学技术
中國安全生產科學技術
중국안전생산과학기술
JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY
2014年
10期
154-159
,共6页
王海峰%李夕兵%董陇军%刘抗%仝慧贤
王海峰%李夕兵%董隴軍%劉抗%仝慧賢
왕해봉%리석병%동롱군%류항%동혜현
支持向量机%采空区稳定性%未确知测度%分级
支持嚮量機%採空區穩定性%未確知測度%分級
지지향량궤%채공구은정성%미학지측도%분급
support vector machine%goaf stability%uncertainty measurement%classification
针对采空区稳定性分级的影响因素众多且关系复杂的特点,提出采用支持向量机理论对采空区稳定性进行分级。根据分级评价指标选取原则,选取岩体结构、地质构造、岩石的质量指标、地下可见水、地下水体、周边开采的影响、相邻空区的情况、工程布置、跨度、面积、高度、矿柱的尺寸及布置、埋藏深度和采空区的规格14个影响因子,建立了采空区稳定性评价指标体系,引入支持向量机理论,选择有向无环图方式构造多类分类器,得到采空区稳定性分级的支持向量机模型。将该模型用于山东黄金矿业西山矿区的25个采空区进行分级,并与未确知测度方法的分级情况进行比较,结果表明:该方法科学合理,意义明确,计算结果更能反映采空区稳定性的实际情况,可以在实际工程中进行推广应用。
針對採空區穩定性分級的影響因素衆多且關繫複雜的特點,提齣採用支持嚮量機理論對採空區穩定性進行分級。根據分級評價指標選取原則,選取巖體結構、地質構造、巖石的質量指標、地下可見水、地下水體、週邊開採的影響、相鄰空區的情況、工程佈置、跨度、麵積、高度、礦柱的呎吋及佈置、埋藏深度和採空區的規格14箇影響因子,建立瞭採空區穩定性評價指標體繫,引入支持嚮量機理論,選擇有嚮無環圖方式構造多類分類器,得到採空區穩定性分級的支持嚮量機模型。將該模型用于山東黃金礦業西山礦區的25箇採空區進行分級,併與未確知測度方法的分級情況進行比較,結果錶明:該方法科學閤理,意義明確,計算結果更能反映採空區穩定性的實際情況,可以在實際工程中進行推廣應用。
침대채공구은정성분급적영향인소음다차관계복잡적특점,제출채용지지향량궤이론대채공구은정성진행분급。근거분급평개지표선취원칙,선취암체결구、지질구조、암석적질량지표、지하가견수、지하수체、주변개채적영향、상린공구적정황、공정포치、과도、면적、고도、광주적척촌급포치、매장심도화채공구적규격14개영향인자,건립료채공구은정성평개지표체계,인입지지향량궤이론,선택유향무배도방식구조다류분류기,득도채공구은정성분급적지지향량궤모형。장해모형용우산동황금광업서산광구적25개채공구진행분급,병여미학지측도방법적분급정황진행비교,결과표명:해방법과학합리,의의명학,계산결과경능반영채공구은정성적실제정황,가이재실제공정중진행추엄응용。
For the reason that many factors with complex relationship influence the classification of goaf stability , the method of support vector machine was proposed .The 14 indexes i.e., rock structure, geological structure, quality indicators of rocks , visible underground water , groundwater body , effect of peripheral mining , engineering layout, span, area, height, pillar size and layout, buried deep, specification of goaf were selected to establish the index system for evaluation based on the selection principle of grading index .A comprehensive classification model of goaf stability was established by the theory of support vector machine with directed acyclic graph .This model was employed to classify 25 goafs in Xishan mine of Shandong Gold Mining , and the classification states were compared with that by the unascertained measure classification method .The results showed that support vector machine is rea-sonable , better reflects the practice and can be applied to the actual engineering .