基于模糊神经网络的煤层冲击地压预测模型研究  

Research of Prediction Model of Bumping Pressure in Coal Layers Based on Fuzzy Neural Network

作　　者：刘晓悦[1] 

机构地区：[1]中国矿业大学(北京校区)煤炭资源与安全开采国家重点实验室

出　　处：《工矿自动化》2008年第1期8-11,共4页Journal Of Mine Automation

基　　金：国家自然科学基金资助项目(50674093)

摘　　要：煤层冲击地压是煤矿重大灾害之一。冲击地压的发生是由多方面因素造成的,具有模糊性、动态性,表现为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。文章提出了多源信息融合的模糊神经元网络算法,且基于势场拓扑层次聚类融合FCM算法的聚类思想,将模糊集合理论引入神经元网络,构成基于多判据信息融合的模糊神经元网络模型,并对该网络进行了优化。通过仿真试验,验证了该模型的有效性。The bumping pressure in coal layers is one of the major disasters in coal mine. 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. This paper presented a fuzzy neural network algorithm of multi-source information fusion, which based on the clustering idea of integrating potential field topology, hierarchical clustering algorithm and FCM algorithm and introduced the fuzzy set theory into neural network to form a multi-criteria fuzzy neural network model based on information fusion, and optimized the network. Simulation showed that the model was valid.

关 键 词：煤矿 煤层 冲击地压 预测模型 信息融合 模糊神经元网络 势场算法 层次聚类 FCM算法 

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]