Posibilidades de un modelo sustituto de incendios mediante el empleo de redes neuronales

In recent years there has been extensive development of the fire computer models, and its use in the study of the fire safety, fire investigation, etc. has been increased. The most important types of fire computer models are the field model and the zone model. The first model reaches a better approximation to fire dynamics, but the second one requires less computational time.Additionally, in the last years, it should be noted the great advances in information processing using artificial neural networks, and it has become a useful tool with application in very diverse fields.This paper analyzes the possibilities of develop a new fire computer model using artificial neural networks. In the first approach to this objective, a simple compartment was analyzed with a field model. After that, simulations employing General Regression Neural Network were performed. This method achieves similar results that the field model employing computational times closer to the zone models. The neural network has been trained with FDS field model and validating the resulting model with data from a full scale test. In later stages other phenomena and different types of networks will be evaluated.