Predictive Maintenance of Cloud-based Machine Learning Infrastructure
Abstract
This paper focuses on predictive maintenance of cloud-based machine learning infrastructure, analyzing its multi-layered architecture and exploring key technical methods, including data collection and preprocessing, machine learning algorithm applications, and model
evaluation and optimization, while validating their effectiveness through practical application scenarios. Research indicates that predictive
maintenance can effectively reduce failure risks, enhance system stability and resource utilization rates, serving as a key means to ensure the
reliability of cloud machine learning infrastructure.
evaluation and optimization, while validating their effectiveness through practical application scenarios. Research indicates that predictive
maintenance can effectively reduce failure risks, enhance system stability and resource utilization rates, serving as a key means to ensure the
reliability of cloud machine learning infrastructure.
Keywords
Cloud machine learning infrastructure; Predictive maintenance; Data preprocessing; Machine learning algorithms
Full Text:
PDFReferences
[1] Li Jieqi, Hu Liangbing. A Review of Equipment Predictive Maintenance Methods Based on Machine Learning[J]. Computer Engineering and Applications, 2020, 56(21): 9-10.
[2] Yin Qingshan, Li Rui, Wang Jianhua. A Method for Equipment Predictive Maintenance Based on Multi-modal Machine Learning:
CN202011191238.9
[3] Wu Shaohan, Hu Zhangfeng, Ren Qiuzheng. A Predictive Maintenance Method and System for Network Equipment:
CN202411238911.8.
[4] Zhao Kunhao, Zhang Bo. Intelligent Monitoring and Fault Prevention in Distribution Network Automation Operation and
Maintenance[J]. Communications World, 2023, 30(10): 73-75.
DOI: http://dx.doi.org/10.70711/aitr.v2i11.7412
Refbacks
- There are currently no refbacks.
