粗糙集-神经网络理论在矿井通风系统评价中的应用  

The application of rough sets-neural network theory to mine ventilation system evaluation

作　　者：王宏图[1,2] 黄振华[1,2] 范晓刚[2] 袁志刚[1,2] 江记记[1,2] 

机构地区：[1]重庆大学煤矿灾害动力学与控制国家重点实验室,重庆400044 [2]重庆大学复杂煤气层瓦斯抽采国家地方联合工程实验室,重庆400044

出　　处：《重庆大学学报（自然科学版）》2011年第9期90-94,共5页Journal of Chongqing University

基　　金：国家自然科学基金资助项目(50774106);国家自然科学创新群体基金资助项目(50921063);国家重点研究发展规划资助项目(2005CB221502);川煤集团科技项目(2009-08)

摘　　要：针对矿井通风系统神经网络评价法中建立样本的不稳定性问题,开展了基于粗糙集和BP神经网络理论的通风系统综合评价研究。以某矿井通风系统为研究对象,应用粗糙集数据分析系统对矿井通风系统评价指标的原始数据样本的分类质量进行了检验;在此基础上,基于人工神经网络理论,建立了矿井通风系统的粗糙集-神经网络评价模型,从而形成了一种新的基于粗糙集-神经网络理论的矿井通风系统评价方法。研究结果表明,经过模型的数据检验和应用性验证,其理论评价结果与实际情况相符,且网络总误差小于0.004;这说明基于粗糙集-神经网络的综合评价方法在矿井通风系统评价中有很好的实际应用效果。To solve the instability problem of established sample in the neural network evaluation method for mine ventilation system,a comprehensive evaluation of the ventilation system is carried out based on rough sets and BP neural networks.Taking the ventilation system of a mine as an example,the classification quality of raw data samples are tested by using rough set data analysis system.Then,based on artificial neural network theory,a rough sets-neural network evaluation model of a mine ventilation system is established and a new rough sets-neural network evaluation method of mine ventilation system is formed.The results show that,after the model validation of data and application,its theoretical evaluation results are in line with the actual situation,and the network total error is less than 0.004.It shows that the comprehensive evaluation method based on rough sets-neural networks has a good effect in evaluating mine ventilation system in practical application.

关 键 词：煤矿 粗糙集 BP神经网络 矿井通风系统 

分 类 号：TD712[矿业工程—矿井通风与安全]