CIVILICA We Respect the Science
(ناشر تخصصی کنفرانسهای کشور / شماره مجوز انتشارات از وزارت فرهنگ و ارشاد اسلامی: ۸۹۷۱)

ANALYSIS OF DOUBLE-LAYER BARREL VAULTS USING DIFFERENT NEURAL NETWORKS; A COMPARATIVE STUDY

عنوان مقاله: ANALYSIS OF DOUBLE-LAYER BARREL VAULTS USING DIFFERENT NEURAL NETWORKS; A COMPARATIVE STUDY
شناسه ملی مقاله: JR_IJOCE-11-1_007
منتشر شده در در سال 1399
مشخصات نویسندگان مقاله:

A. Kaveh
A. Eskandari

خلاصه مقاله:
The artificial neural network is such a model of biological neural networks containing some of their characteristics and being a member of intelligent dynamic systems. The purpose of applying ANN in civil engineering is their efficiency in some problems that do not have a specific solution or their solution would be very time-consuming. In this study, four different neural networks including FeedForward BackPropagation (FFBP), Radial Basis Function (RBF), Extended Radial Basis Function (ERBF), and Generalized Regression Neural Network (GRNN) have been efficiently trained to analyze large-scale space structures specifically double-layer barrel vaults focusing on their maximum element stresses. To investigate the efficiency of the neural networks, an example has been done and their corresponding results have been compared with their exact amounts obtained by the numerical solution.

کلمات کلیدی:
structural analysis, double-layer barrel vaults, neural networks, feedforward backpropagation, radial basis function, extended radial basis, generalized regression neural network, element stresses

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1831220/