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论文类型：会议论文

发表时间：2008-10-12

收录刊物：EI、Scopus

摘要：The stope structure parameters and grade indices of underground metal mine are concerned to the safety, economy and sociality of the whole mine. The conventional methods to ascertain above parameters are generally according to experience and analogy, which has artificial blindness. Metal mine exploitation is a complex system engineering, the whole mine system includes many subsystems, and some of them has complex nonlinear characteristics. The paper utilizes sublevel caving simulation system and RFPA numerical program to respectively analyze the recovery index and the surrounding rock stability. The ANN model also is used to fitting the nonlinear subsystems such as concentration ratio model because of its self-learning .ability, considering multi-objects including economic efficiency amount of metal and cash flow, proposes the grade indices optimization method. Combining above means, based on database, model base, knowledge base and inference machine, constructs intelligent decision support system. Using the system to appraise the stope structure parameters and optimize the grade indices of Jinshandian Ore Mine of Wuhan City of Hubei Province. It states the method of the paper is feasible, and the analysis results have guiding mean to the ore mine. © 2008 IEEE.