Neuro-fuzzy assessment of building damage and safety after an earthquake

Abstract

This chapter describes the algorithmic basis of a computational intelligence technique, based on a neuro-jilzzy system, developed with the objective ofassisting nonexpert professionals ofbuilding construction to evaluate the damage andsafety ofbuildings after strong earthquakes, facilitating decision-making during the emergency response phase on their habitability and reparability. A hybrid neuro-jilzzy system is proposed, based on a special three-layer feed-forward artificial neural network and fuzzy rule bases. The inputs to the system are jilzzy sets, taking into account that the damage levels ofthe structural components are linguistic variables, defined by means ofqualifications such as slight, moderate or severe, which are very appropriate to handle subjective and incomplete information. The chapter is a contribution to the understanding ofhow soft computing applications, such as artificial neural networks and fuzzy sets, can be used to complex and urgent processes of engineering decision-making, like the building occupancy after a seismic disaster.