摘要
根据影响矿井通风系统的各因素,建立了一个基于RBF神经网络的矿井通风系统可靠性评价新模型。利用Matlab编程来确定各个参数,预测速度和精度明显提升,同时还使操作流程简化。经检验,实际情况与预测结果相符,所建立的RBF神经网络完全可以映射系统的可靠性等级,该方法简单易操作,有一定的应用价值。
According to various factors of affecting the mine ventilation system, established a reliability evaluation new model of mine ventilation system based on RBF neural network. Using Matlab programming to determine various parameters to improved the speed of predicting and accuracy significantly, and also makes the operation process is simplified. Upon examination, the actual situation is consistent with the predicted results, the established RBF neural network can map the system reliability level, the method is simple and easy to operate, there is a certain value.
出处
《煤矿机械》
2015年第2期248-250,共3页
Coal Mine Machinery
基金
安徽省高校省级自然科学研究项目(KJ2012B062)
关键词
RBF神经网络
矿井通风系统
可靠性评价
RBF neural network
mine ventilation system
reliability evaluation
