Optimal Selection of the Maintance Method for Existing Bridge Decks Using Artificial Neural Network

The purpose of this study is to analysis the original problem of current equipments, and to improve restoration methods. The deterioration process, cause of damage, and the fatigue mechanism of RC slabs were analysed. Also, the condition of RC slab was classified for the applied load. Artificial neural networks are not only efficient calculating methods but also widely used to solve the complex problems at many construction sites. This study examines at existing R.C bridge decks and needs the damage form, the damage cause, and the artificial neural network's form. The 36 database networks were used in this study. This study evaluates a integrity assessment model for external conditions generally the way of 4 steps' ageing. Each method of constructions fixed damage & recovery effect is able to predict and evaluate cost of repair works which is base on repairing and reinforcing method of constructions. Also, it can measure structures about before and after the remainder life.