摘要
介绍了模糊综合评判和人工神经网络原理,分析了一般BP神经网络在研究复杂性问题时存在的局限性,根据模糊人工神经网络模型的构建方法,探讨了该模型在矿井构造定量评价中的应用,结合鲍店煤矿的实际资料,对建立的模糊人工神经网络模型进行了学习训练,对未采区的构造复杂程度进行了预测,结果表明:模糊人工神经网络较一般BP神经网络具有更快的收敛速度和更准确的预测效果.
The principle of fuzzy comprehensive assessment and artificial neural network is presented. The limitation of general BP neural network in studying the complex question is analyzed. According to the construction method of fuzzy artificial neural network （FANN） model, its application in quantitative evaluation of mine structure is discussed. Combined with the real data of BaoDian Coal Mine, the model of FANN is set up and trained to predict the complexity of mine structure in non-exploiting field. The result shows that the convergence speed of FANN is fast and the effect of prediction is better than general BP neural network.
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2005年第5期609-612,共4页
Journal of China University of Mining & Technology
关键词
模糊人工神经网络
BP神经网络
模糊综合评判
矿井构造
定量评价
fuzzy artificial neural network
BP neural network
fuzzy comprehensive assessment
mine structure
quantitative evaluation
