The Model for Risk Evaluation of Urban Fire Based on Neural Network and Genetic Algorithms
Wang Cong-lu · Zhongguo anquan kexue xuebao · 2006
According to fire control safety engineering and systematic safety engineering theory,risk evaluation index system for urban region fire is established based on the situation of cities' development of our country and the fire control safety management.Aiming at the irrational distribution of weight value of evaluation index caused by neural network's liability to local minimum,a new model for risk assessment of urban fire is established based on neural network and genetic algorithms.In this model,the likelihood of fire occurring and the severity caused by fire are regarded as input parameters and fire risk grade as output parameter.By adopting error-inverse arithmetic to train BP network,the risk grade range of fire is obtained,which effectively solves the dynamic and non-linear characteristics of urban fire.Illustration shows this model is feasible and can give a good reference to safety management of urban fire control.