Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Study of intelligent load analysis system using genetic algorithm

Authors
Jo, Byung-WanYoon, Kwang-WonLee, Yun-SungChoi, Ji-Sun
Issue Date
Aug-2014
Publisher
Institution of Engineering and Technology
Citation
IET Intelligent Transport Systems, v.8, no.5, pp 464 - 469
Pages
6
Indexed
SCIE
SCOPUS
Journal Title
IET Intelligent Transport Systems
Volume
8
Number
5
Start Page
464
End Page
469
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/202724
DOI
10.1049/iet-its.2012.0142
ISSN
1751-956X
1751-9578
Abstract
Roads play a crucial role in societal infrastructure as a main artery for the economy and lives of people. However, numerous deformations are caused by an increasing number of overloaded vehicles. Accordingly, an efficient managing system for preventing overloaded vehicles could be organised by using the road as a scale by applying a genetic algorithm to analyse the load and drive information of vehicles. First, accurate analysis of loads by using the behaviour of the road itself is needed to solve illegal axle manipulation problems of overloaded vehicles and to install intelligent embedded load analysis systems. Accordingly, to use the road behaviour, the transformation in this way was measured by installing an underground box-type indoor model, and an indoor experiment was conducted by using a genetic algorithm. After five driving sessions with each vehicle, 50 sets of dynamic responding data were attained. The recognition variables were calculated to be within the error range of 10%.
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 건설환경공학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE