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Explores optimizing vehicle design parameters using neural networks, suggesting improved accuracy in resource estimation.
The paper considers the key parameters of the technical requirement for vehicle designing using neural networks and the main criteria for their optimality, as well as describes the processes of predicting the aggregate resource based on neural networks, which increase the accuracy of estimates and the quality of design. The technical requirement parameters are clarified based on the UAZ-3303 vehicle. Data on the resources of individual aggregates are provided.
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Dyakov et al. (2026) studied this question.
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