Abstract

The article examines an approach to increasing the safety of a vehicle's design with the help of artificial neural networks (ANNs) integrated in the vehicle's self-diagnostic system. Solving this problem will require the vehicle's self-diagnostic system to be provided with a database with numerous states so that each information parameter can be assessed in terms of its impact on the probability of transition of the vehicle into some state. ANNs will help to correct the values of self-diagnostic output signals for prompt maintenance and current repairs as well as safe operation of the vehicle.

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