Classification of regional risk priorities of reinforced concrete structures with a hybrid artificial intelligence model

The structural losses caused by the last 06 February 2023 Kahramanmaraş earthquake couple once again revealed the importance of earthquake performances of existing structures. A part of modern pre-disaster management is to determine the risk priorities of existing structures before a possible earthquake and to ensure that necessary precautions are taken. In this thesis study, exemplification was made on the existing reinforced-concrete building stock in Çaldıran district of Van province in order to determine the risk priorities of reinforced-concrete buildings with artificial neural networks. Structural system scores were obtained for selected reinforced-concrete buildings using the data obtained from field investigations. Within the scope of the study, the Turkish Rapid Assessment method was used which was updated in 2019. The regional risk priorities of reinforced-concrete buildings were tried to be determined with the help of artificial neural network, taking into account all the obtained values. Information about the building stock of the region was given and suggestions were made about the measures that could be taken.