دوره 12، شماره 1 - ( 10-1400 )                   جلد 12 شماره 1 صفحات 89-69 | برگشت به فهرست نسخه ها

XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Sarjamei S, Sajjad Massoudi M, Esfandi Sarafraz M. DAMAGE DETECTION OF TRUSS STRUCTURES VIA GOLD RUSH OPTIMIZATION ALGORITHM. International Journal of Optimization in Civil Engineering 2022; 12 (1) :69-89
URL: http://ijoce.iust.ac.ir/article-1-505-fa.html
DAMAGE DETECTION OF TRUSS STRUCTURES VIA GOLD RUSH OPTIMIZATION ALGORITHM. عنوان نشریه. 1400; 12 (1) :69-89

URL: http://ijoce.iust.ac.ir/article-1-505-fa.html


چکیده:   (5409 مشاهده)
The damage identification of truss constructions was investigated in this work. Damage detection is defined through an inverse optimization problem. A function defined as a combination of mode shapes and natural frequencies is examined to minimize damage structures. This guided approach considerably reduces the computational cost and increases the accuracy of optimization. This index mostly exhibits an acceptable performance. Gold Rush Optimization (GRO), an artificial intelligence system based on the power of human thinking and decision-making, was employed to address damage detection. The programming was done in MATLAB. Validation and verification were carried out using a 10, 25, 200, 272, and 582 bar truss. A comparison between the GRO, MCSS, PSO and TLBO is conducted to show the efficiency of the GRO in finding the global optimum. The results show that utilizing the proposed function and the GRO optimization technique to discover truss damaged structure in the quickest time possible is both reliable and stable.
متن کامل [PDF 1321 kb]   (2524 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: Applications
دریافت: 1400/11/2 | پذیرش: 1400/10/30 | انتشار: 1400/10/30

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به دانشگاه علم و صنعت ایران می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb