Abstract
The objective of the research is to prove the capability of Self-Organizing Map (SOM) to classify brake formula of a vehicle on a bank of roller tester from the MOT (Ministry of transport) and on flat ground. The neural network demonstrated good generation of the brake-slide relationship when presented with data not used in network training. This tool will easily find brake-slide equation of each experience and we will compare the brake on two different experimental tests. This article demonstrates that the MOT brake testing do not check the car brake in its usual way of driving. We will provide data and graphs to prove that tyre pressure is a determining factor when assessing the condition of brakes.
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Senabre, C., Velasco, E., Valero, S. (2010). SOM for Getting the Brake Formula of a Vehicle on a Brake Tester and on Flat Ground. In: de Leon F. de Carvalho, A.P., Rodríguez-González, S., De Paz Santana, J.F., Rodríguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14883-5_52
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DOI: https://doi.org/10.1007/978-3-642-14883-5_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14882-8
Online ISBN: 978-3-642-14883-5
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