Investigation the variation of vertical vibrations of vehicles using neural networks

Farzad Khalili Esfahani¹ Mohsen Heydari Beni² Hessam Zabihi³ Amir Hossein Mohammad Shafiee⁴

1) Lecturer, Electrical Engineering Depatment, Institute of Higher Education of Naghsh –e- Jahan, Isfahan.
2) M.Sc Student of Mechanical Engineering, Faculty of Engineering, Shahrekord University, Shahrekord, Iran.
3) B.Sc Student of Mechanical Engineering, Faculty of Engineering, Shahrekord University, Shahrekord, Iran.
4) M.Sc Student of Mechanical Engineering, Faculty of Engineering, Shahrekord University, Shahrekord, Iran.

Publication : 3rd International Conference On Research Science And Technology(3rstconf.com)
Abstract :
In this study, vertical vehicle vibrations are studied using random theory, and some back propagation artificial neural networks (ANNs) with four functions such as newff, newelm,newcf, and newfftd are also employed to predict amplitudesof accelerations of vehicles for different road conditions. Based on the test results of each network with some data set, different from those used in the training phase, it was shown that newelm function neural model has superior performance than newff, newcf, and newfftd functions and can predict outputs in a wide range of vehicle vibration conditions with reasonable accuracy.
Keywords : neural networks vertical vibrations random theory.