Prediction of Equipment Consumption Based on LASSO Regression and Markov Chain Models
By analyzing the influencing factors of equipment spare parts consumption, dividing the historical consumption data of equipment spare parts into training set and test set, using the training set to establish LASSO regression model, initially predicting the consumption of equipment spare parts, and then using the Markov chain, correcting the predicted consumption, it is shown that through calculations, the method has substantially reduced the average relative error of the prediction of both the training set and the test set and improved the prediction accuracy, which is of great significance for improving the quality of equipment protection.
Authors
- Xuexin Zhang (ORCID: https://orcid.org/0000-0002-5685-8829)
Institutions
- Changchun 208 Hospital (CN)
Publication Details
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1109/icbaie63306.2024.11116949
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00