Open AccessStudy of intelligent load analysis system using genetic algorithm
Author(s) -
Jo ByungWan,
Yoon KwangWon,
Lee YunSung,
Choi JiSun
Publication year - 2014
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2012.0142
Subject(s) - computer science , genetic algorithm , algorithm , artificial intelligence , machine learning
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%.