Preparation of synthetic data to be used as inputs for neural network using CAD system
- DOI
- 10.2991/978-94-6463-423-5_39How to use a DOI?
- Keywords
- frame; artificial intelligence; generative design; Creo
- Abstract
The aim of the work was to create input data for the neural network. A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. A neural network needs a large amount of data to be properly trained. Creo was used as a tool, which has a generative design tool in it that brings several significant benefits. The output of generative design is usually dozens of different design options, which the designer only must evaluate based on various criteria and choose the most suitable design. Primarily, it is used to reduce weight by approximately 30 to 40% compared to a conventional design. The lower weight not only brings material savings, but above all increased functionality of the components, which can achieve higher speeds and accelerations due to lower momentum, etc. The subject of the generation was the frame of the bicycle. A set of designs were generated that meet the input criteria and then will be used to train the neural network.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jozef Ondriga AU - Jozef Jenis AU - Jakub Fiacan AU - Slavomir Hrcek AU - Michal Lukac PY - 2024 DA - 2024/05/22 TI - Preparation of synthetic data to be used as inputs for neural network using CAD system BT - Proceedings of the 62nd International Conference of Machine Design Departments (ICMD 2022) PB - Atlantis Press SP - 344 EP - 354 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-423-5_39 DO - 10.2991/978-94-6463-423-5_39 ID - Ondriga2024 ER -