FANN模型在金属矿冲击地压预测中的应用  

Application of FANN in Prediction of Bumping Pressure in Metal Mine

作　　者：李文秀[1] 孟庆立[1] 吉占华[1] 王山山[1] 汪崎[1] 

机构地区：[1]河北大学建筑工程学院,河北保定071002

出　　处：《模糊系统与数学》2010年第5期156-160,共5页Fuzzy Systems and Mathematics

基　　金：河北省科学技术攻关项目(072156142);河北省教育厅科研项目(2007415)

摘　　要：金属矿山冲击地压是采矿工程中所涉及到的重大灾害之一。冲击地压的发生是由多方面因素造成的,具有动态和模糊性,在客观上属于一个复杂的非线性动力学过程,这使得冲击地压预测系统的数据处理不能按照常规的线性系统法进行处理。根据模糊神经网络理论,本文给出了多源信息融合的模糊人工神经网络(FANN)模型。通过具体工程应用,说明了本文分析模型的正确性和有效性。The bumping pressure in metal mine is one of the major disasters mining engineering.The accident is caused by many factors.It is ambiguous and dynamic,and expresses as a complex nonlinear dynamic process.This makes data processing system for bumping pressure forecasting can not be processed with the conventional linear system.According to fuzzy mathematics and neural network theories,the fuzzy artificial neural network（FANN） model of multi-source information fusion is given.Finally,an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

关 键 词：模糊数学 采矿工程 金属矿山 冲击地压 模糊人工神经网络 

分 类 号：TD324[矿业工程—矿井建设] TP273[自动化与计算机技术—检测技术与自动化装置]