基于神经网络的矿井通风系统安全评价及实践研究
Research on Safety Evaluation and Practice of Mine Ventilation System Based on Neural Network
张杰1
作者信息
- 1. 山西世德孙家沟煤矿有限公司,山西 忻州 036604
- 折叠
摘要
基于传统BP神经网络模型存在的不足,介绍一种径向基函数神经网络模型,以此实施矿井通风系统安全评价.具体研究中需先构建径向基函数神经网络模型,并对神经网络学习算法进行数学解释.将径向基神经网络模型应用于矿井通风系统安全评价分析,初步确认应用可行性后,将形成的矿井通风系统安全评价方法应用于工程实践,进一步确认基于径向基函数神经网络模型的矿井通风系统安全评价方案的应用价值.
Abstract
Based on the shortcomings of traditional BP neural network models,a radial basis function neural network model is introduced to implement safety evaluation of mine ventilation systems.In specific research,it is necessary to first construct a radial basis function neural network model and provide a mathematical explanation for the neural network learning algorithm.After applying the radial basis function neural network model to the safety evaluation analysis of the mine ventilation system and confirming its feasibility,the formed safety evaluation method for the mine ventilation system will be applied to engineering practice,further confirming the application value of the safety evaluation scheme for the mine ventilation system based on the radial basis function neural network model.
关键词
神经网络/矿井通风系统/安全评价/工程实践Key words
neural network/mine ventilation system/safety evaluation/engineering practice引用本文复制引用
出版年
2024
NETL
NSTL
万方数据