دوره 13، شماره 2 - ( 1-1402 )                   جلد 13 شماره 2 صفحات 154-143 | برگشت به فهرست نسخه ها

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Kaveh A, Seddighian M R, Farsi N. A METAHEURISTIC-BASED ARTIFICIAL NEURAL NETWORK FOR PLASTIC LIMIT ANALYSIS OF FRAMES. International Journal of Optimization in Civil Engineering 2023; 13 (2) :143-154
URL: http://ijoce.iust.ac.ir/article-1-546-fa.html
A METAHEURISTIC-BASED ARTIFICIAL NEURAL NETWORK FOR PLASTIC LIMIT ANALYSIS OF FRAMES. عنوان نشریه. 1402; 13 (2) :143-154

URL: http://ijoce.iust.ac.ir/article-1-546-fa.html


چکیده:   (4845 مشاهده)
Despite the advantages of the plastic limit analysis of structures, this robust method suffers from some drawbacks such as intense computational cost. Through two recent decades, metaheuristic algorithms have improved the performance of plastic limit analysis, especially in structural problems. Additionally, graph theoretical algorithms have decreased the computational time of the process impressively. However, the iterative procedure and its relative computational memory and time have remained a challenge, up to now. In this paper, a metaheuristic-based artificial neural network (ANN), which is categorized as a supervised machine learning technique, has been employed to determine the collapse load factors of two-dimensional frames in an absolutely fast manner. The numerical examples indicate that the proposed method's performance and accuracy are satisfactory.
 
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نوع مطالعه: پژوهشي | موضوع مقاله: Applications
دریافت: 1401/10/8 | پذیرش: 1401/10/21 | انتشار: 1401/10/21

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