Equipment Management Performance Evaluation Method Based on Improved Wavelet Neural Network
- DOI
- 10.2991/978-94-6463-256-9_91How to use a DOI?
- Keywords
- equipment management; performance evaluation; neural network
- Abstract
Because there are many factors affecting enterprise equipment management, the performance evaluation of equipment management is uncertain, and the existing evaluation methods are too subjective. In order to improve this problem, this paper proposes a new method of equipment management performance evaluation using sparrow search algorithm to improve wavelet neural network. Firstly, according to the characteristics of equipment management, the performance evaluation index system of equipment management is established. Secondly, the Sparrow Search Algorithm is used to improve the evaluation accuracy and convergence speed of the Wavelet Neural Network. Finally, the equipment management performance evaluation model is constructed, and the case analysis is carried out. The analysis shows that compared with other neural networks, the improved Wavelet Neural Network has faster convergence speed and better fitting effect, and can effectively carry out equipment management performance evaluation.
- 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 - Lili WANG AU - Liang YOU AU - Zhongyi CAI AU - Jiangang JIN PY - 2023 DA - 2023/10/09 TI - Equipment Management Performance Evaluation Method Based on Improved Wavelet Neural Network BT - Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023) PB - Atlantis Press SP - 925 EP - 935 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-256-9_91 DO - 10.2991/978-94-6463-256-9_91 ID - WANG2023 ER -