The prediction of damage condition for light structures with hybrid artificial intelligence technique

A review of existing literature in the area of expansive soils showed a lack of a thorough scientific diagnostic of the damage to light structures founded on them. A database of the records of damage to light structures in Victoria, Australia was examined with a view to determining the factors which most influenced the cracking of the structures over time. This database recorded damage as and when it was reported by the occupants. The aim of this paper is to develop a model to predict the damage condition of light structure on expansive soils in Victoria using a hybrid Artificial Intelligence technique. The result from the analysis of the model is promising. It demonstrated that the model is able to resolve the problems facing light structures on expansive soils. The model is able to predict the damage condition or damage class using different combinations of factors