دوره 13، شماره 2 - ( 1-1402 )
جلد 13 شماره 2 صفحات 154-143 |
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Kaveh A, Seddighian M R, Farsi N. A METAHEURISTIC-BASED ARTIFICIAL NEURAL NETWORK FOR PLASTIC LIMIT ANALYSIS OF FRAMES. IJOCE 2023; 13 (2) :143-154
URL: http://ijoce.iust.ac.ir/article-1-546-fa.html
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
چکیده: (8372 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.
نوع مطالعه: پژوهشي |
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دریافت: 1401/10/8 | پذیرش: 1401/10/21 | انتشار: 1401/10/21
دریافت: 1401/10/8 | پذیرش: 1401/10/21 | انتشار: 1401/10/21
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