# A Hybrid ANN-GA Model for an Automated Rapid Vulnerability Assessment of Existing RC Buildings
## 6 Discussion and Conclusions  
In the pre-disaster preparation phase of modern disaster management, one of the processes is to decide whether the seismic performance of the building stock in the region that might be affected by the earthquake is sufficient. In light of this information, it is necessary to determine the buildings with insufficient earthquake performance and decide on demolition and retrofitting when necessary. Many buildings in stock do not make detailed structural analyses for individual structures possible. Thus, simplified approaches are specified to minimize the number of buildings in large stock for further comprehensive, advanced analyses. For the first time in Turkey, risk prioritization of buildings has been defined under PDRB-2013 for different building types. This study used the rapid assessment method for RC structures in this regulation. One of the limitations of using this method is that RC structures are between 1-7 stories. This method is not used in RC structures with more than 7-stories. Within the scope of this study, 329 RC buildings in the province of Bitlis, located in the Lake Van Basin, which has a high seismic risk in Turkey, were considered. While selecting these buildings, each neighborhood in the city center of Bitlis was taken into account. In order to adequately represent the building stock in each neighborhood, an average of 25 RC buildings was selected where the method can be applied. The short column in 58%, soft/weak story in 63%, heavy overhang in 66%, collision effect in 69%, and hill-slope effect in 22% of the buildings has been examined. The existence of any or a combination of these negative features in structures will directly affect their seismic behavior. Since these parameters, which are taken into account in the rapid assessment method, are obtained using post-earthquake damage data, they provide information about the behavior of structures under the influence of possible earthquakes. Especially, the existence of soft story and heavy overhang damages are commonly observed in earthquakes. In addition, the quality of the building is also significant under the effect of earthquakes. The negativity score recommended for the soft story and overhang in this rapid evaluation method reveals the vulnerability of this negativity parameter. Another vulnerable parameter is the visual quality of the building. The presence of one of them alone increases the earthquake vulnerability and increases the risk priority. The presence of several of them together will increase the earthquake vulnerability even more. Therefore, it is necessary to avoid these parameters as much as possible during the building design phase. However, if making these negative parameters is necessary, the structural design should be done by taking the necessary precautions. Care should be taken to ensure that the criteria, such as sufficient strength, continuity, and ductility, are at the levels stipulated in earthquake regulations. Risk priorities can be determined on a regional basis based on performance scores obtained for the buildings. Therefore, it helps to identify the necessary buildings and prioritize the detailed analysis. These performance score results can only be used to determine risk priorities for RC. Therefore, it cannot surely be decided whether the risky buildings comply with the earthquake regulations. This is just a rapid assessment, as stated in the earthquake code. Therefore, the final results of the structures are determined from a detailed analysis. In line with the purpose of this study, the most optimal ANN model was created with a hybrid structure to quickly and easily calculate the structural result scores used in determining the regional earthquake risk priorities of RC buildings. A feedforward back-propagation ANN model was implemented to estimate the earthquake score within the created model. The network parameters in the ANN structure directly affect the network's efficiency.