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篇名
Method for Predicting and Evaluating Post Earthquake Damage of Urban Buildings Based on Artificial Intelligence Algorithms
並列篇名
Method for Predicting and Evaluating Post Earthquake Damage of Urban Buildings Based on Artificial Intelligence Algorithms
作者 Jian-Ming Yu (Jian-Ming Yu)Ke Zhang (Ke Zhang)Jian-Zhong Zhang (Jian-Zhong Zhang)Feng Xue (Feng Xue)Wei Liu (Wei Liu)
英文摘要

This article mainly focuses on the damage assessment of buildings after earthquakes. Firstly, a structural damage model was established based on most reinforced concrete buildings and described using a function. Then, a BP neural network was used to solve the function. Traditional neural networks are prone to falling into local optima. Therefore, in order to improve the performance of neural networks, cross fusion with genetic algorithms is used to avoid falling into local optima, Improve the efficiency of the algorithm. Finally, through experimental verification, the proposed method can quickly evaluate the damage of building structures, with an accuracy rate of 97%.

 

起訖頁 185-193
關鍵詞 damage assessmentBP neural networkgenetic algorithmstructural damage
刊名 電腦學刊  
期數 202308 (34:4期)
該期刊-上一篇 Machine Vision Based Defect Detection Method for Electronic Component Solder Pads
該期刊-下一篇 Research on the Construction and Application of Knowledge Graph of Digital Resources in Vocational Colleges
 

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