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  5. Adaptive neural-fuzzy inference system based method to modeling of vehicle crash

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Article
English
2013

Adaptive neural-fuzzy inference system based method to modeling of vehicle crash

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English
2013
Vol 1746
Vol. 1746
DOI: 10.1109/icmech.2013.6518565

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Hamid Reza Karimi
Hamid Reza Karimi

Politecnico di Milano

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Lin Zhao
Witold Pawlus
Hamid Reza Karimi
+1 more

Abstract

Various areas of research need to be considered in order to establish a mathematical model of a vehicle crash. To enhance the modeling process, a novel ANFIS-based approach to reconstruct behavior of impacting vehicles is presented in this paper. Kinematics of center of gravity (COG) a vehicle involved in an oblique barrier collision is reproduced by application of a five-layered ANFIS structure. Then, the same ANFIS system is used to simulate a different collision type than the one which was used in the training stage. The points of interests are selected to be the locations of accelerometers mounting. The accuracy of the proposed method is evaluated by the comparative analysis with the reference measurements from full-scale vehicle collisions.

How to cite this publication

Lin Zhao, Witold Pawlus, Hamid Reza Karimi, Kjell G. Robbersmyr (2013). Adaptive neural-fuzzy inference system based method to modeling of vehicle crash. , 1746, pp. 370-375, DOI: 10.1109/icmech.2013.6518565.

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Publication Details

Type

Article

Year

2013

Authors

4

Datasets

0

Total Files

0

Language

English

DOI

10.1109/icmech.2013.6518565

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