Applying BP neural network in high-rising buildings fire risk assessment

This paper is concerned with the problem of applying BP neural network in high-rising buildings fire risk assessment. By using the back propagation (BP) neural network, a smart fire risk estimation model is developed. Based on this model, we can obtain the building´s fire rating, and by analysis the estimation results, we can develop a scheme to guide the decision-makers to improve the building´s fire rating. Finally, the numerical example is given to show the effectiveness of the proposed theorems.