A Hybrid ANN-GA Model for an Automated Rapid Vulnerability Assessment of Existing RC Buildings
نویسندگان
چکیده
Determining the risk priorities for building stock in highly seismic-prone regions and making final decisions about buildings is one of essential precautionary measures that needs to be taken before earthquake. This study aims develop an Artificial Neural Network (ANN)-based model predict reinforced-concrete (RC) constitute a large part existing stock. For this purpose, network parameters structure have been optimized by establishing hybrid with Genetic Algorithm (GA). As result, ANN can make accurate predictions maximum efficiency. The suggested feedforward back-propagation model. It 329 RC most successful way, which performance score was calculated using Turkey Rapid Evaluation Method (2013). In paper, GA-ANN implemented ANN, gene revealed model, produced results calculating score. addition, required input obtaining more efficient solving such problem need used optimized. With help operation process will eliminated. created 98% determining priority buildings.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2022
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app12105138