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Obtaining Modal Parameters in Steel Model Bridge by System Identification using Artificial Neural Networks

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Obtaining Modal Parameters in Steel Model Bridge by System Identification using Artificial Neural Networks


Hakan Aydin



Hakan Aydin "Obtaining Modal Parameters in Steel Model Bridge by System Identification using Artificial Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2, February 2020, pp.438-443, URL: https://www.ijtsrd.com/papers/ijtsrd30013.pdf

Artificial Neural Networks are easy to build and take good care of large amounts of noisy data. They are especially suitable for the solution of nonlinear problems. They work well for problems where domain experts aren't available or there are no known rules. Artificial Neural Networks can also be adapted to civil engineering structures and suffer from dynamic effects. Structures around the world were badly damaged by the earthquake. Thus, loss of life and property was experienced. This particularly affected countries on active fault lines. Pre and post-earthquake precautions have been developed in the world. For these reasons, it is necessary to determine the dynamic performance of structures in the world. There are several methods to determine dynamic performance. System identification is one of these methods. The mathematical model of the structural system is obtained by system identification method. Artificial Neural Networks (ANN) is a system identification method. ANN can adapt to their environment, work with incomplete information, make decisions under uncertainties and tolerate errors. Steel Model Bridge was used in this study. The system identification of the steel model bridge with the ANN method of 0.90 was made successfully. As a result of this study, ANN approach can provide a very useful and accurate tool to solve the problem in modal identification studies.

Steel Model Bridge, System Identification, Artificial Neural Networks, Modal Parameters, Input-Output dimensions


IJTSRD30013
Volume-4 | Issue-2, February 2020
438-443
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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