基于神经网络的重大危险源动态分级研究

Study in Dynamic Risk Classification of Major Hazards Based on Neural Networks

利用自组织神经网络对重大危险源进行动态分级研究，介绍了神经网络的模式聚类即分级法的自组织学习过程和算法，克服了以往危险源分级方法的某些局限性。

By Using self-organized neural network, so called Adaptive Resonance Theory(ART),the dynamic risk classification of major hazards was studied,at the same time the process and algorithm of the dynamic classification method were introduced,by which some shortcomings of traditional means by fixed risk grades were overcome.The method has been simulated on a computer,the results showed that the method is rational and feasible.