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March 17, 2026Russian Engineering Research0 citations

Clarification of the Technical Requirement Parameters for Vehicle Designing Using a Neural Network

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IDI. F. DyakovEDE. V. Dyakova

Key Points

  • The central aim is to clarify technical requirement parameters for vehicle design using neural networks.
  • Analyzed technical requirements for the UAZ-3303 vehicle.
  • Utilized neural networks to predict aggregate resource.
  • Assessed main criteria for optimality in vehicle design.
  • Introduced clarified parameters enhancing vehicle design.
  • Increased accuracy in resource estimates via neural network predictions.
  • Improved design quality based on optimized criteria.

Abstract

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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Cite This Study

Dyakov et al. (2026) studied this question.

synapsesocial.com/papers/69b8f11edeb47d591b8c5ef0https://doi.org/10.3103/s1068798x2570340x
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