Research on Application Methods of Network Fault Prediction Models
DOI:
https://doi.org/10.6911/WSRJ.202408_10(8).0010Keywords:
Network Failure; Prediction Model; Network Monitoring.Abstract
With the rapid development of information technology, the internet has become an indispensable part of our daily life and work. However, the occurrence of network failures often has a significant impact on individuals, businesses, and even the country. Therefore, predicting network failures has become crucial. In recent years, machine learning and artificial intelligence technologies have achieved significant success in many fields, including network fault prediction. This article will explore the construction, application, and optimization of network fault prediction models.
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References
Yang Qingchuan Engine Fault Detection Based on Deep Learning [D]. Hangzhou University of Electronic Science and Technology, 2021. DOI: 10.27075/dc.cnki. ghzdc.2021.000341
Single Triumph Research on Engine Fault Prediction Method Based on Deep Learning [D]. Civil Aviation University of China, 2019. DOI: 10.27627/d.cnki. gzmhy.2019.000271
Mei Benxiang Research on Monitoring and Management System for Vehicle Service Platform Based on MVC Mode [D]. Guangdong University of Technology, 2018
Yu Zhisheng Automotive Theory [M] Version 5 Beijing: Machinery Industry Press, 2009
Hu Tianjie Research on Model Based ECU Hardware in the Loop Simulation [D] Kunming: Kunming University of Technology, 2020
Wang Wangyu Automotive Design [M] Version 4 Beijing: Machinery Industry Press, 2004
Zhang Wenjie, Li Changlong, Hong Yu, et al. The Application of Remote Diagnosis System Based on Big Data Technology in Automobiles [J]. Automotive Digest, 2022 (4): 30-33
Zhang Jiaqi Design and Implementation of a Vehicle Test Management Information System Based on Java Web [D]. Beijing: Beijing Jiaotong University, 2016
Lu Shaobing. Research on Hybrid Language Programming and Its Implementation Based on Python [J]. Science and Technology Information, 2022, 20 (14): 31-33
Zhang Wei. Implementation of Vehicle Detection Algorithm Based on Python [J]. Mechanical Management Development, 2019,34 (12): 258-261
Cheng Xueqi, Jin Xiaolong, Wang Yuanzhuo, et al. Overview of Big Data Systems and Analysis Technology [J]. Journal of Software, 2014,25 (9): 1889-1908
Zhao Li Design and Implementation of Vehicle Monitoring System Based on Big Data Processing [D]. Beijing: Beijing Jiaotong University, 2019
Zeng Xianyu Optimization and Implementation of Vehicle Monitoring System Based on Big Data Technology [D]. Changchun: Jilin University, 2016
Li Guojie, Cheng Xueqi. Big data research: a major strategic area for future science and technology and economic and social development - research status and scientific thinking of big data [J]. Journal of the Chinese Academy of Sciences, 2012, 27 (6): 647-657
Zeng Lei. Review of Big Data Research [J]. Software Guide, 2015,14 (8): 1-2
Fu Yan, Li Hongru. Research on the Digital Transformation System Architecture of Vehicle Enterprises [J]. Automotive Digest, 2022 (7): 20-26
Wang Ruwei The Application of Java Programming Language in Big Data Development [J]. Electronic Technology, 2022, 51 (1): 160-161
Guo Yang, Chang Yingxian. On the Application of Java Language in Computer Software Development [J]. Digital Communication World, 2022 (1): 88-90+94
Zhang Jiaqi Design and Implementation of a Vehicle Test Management Information System Based on Java Web [D]. Beijing: Beijing Jiaotong University, 2016
Li Jian Diagnosis of Gas Path Faults in Variable Cycle Engines Based on Deep Learning [D]. Shanghai Jiao Tong University, 2019. DOI: 10.27307/d.cnki. gsjtu. 2019. 001850
Hong Jiyu Reliability analysis of aircraft engines based on deep learning [D]. Nanjing University of Aeronautics and Astronautics, 2018
Zhou Yiren, Qiu Xiaolin, Guo Zhiqiang. Fault identification of engine valve mechanism based on deep learning theory [J]. Manufacturing Automation, 2017, 39 (11): 89-93
Yan Bing The Application of Deep Learning in Aircraft Engine Fault Diagnosis [D]. Shanghai Jiao Tong University, 2017
Ostrowski K, Birman K, Dolev D. Extensible Architecture for High Performance, Scalable, Reliable Publish Subscription Events and Notification [J] International Journal of Web Services Research, 2007, 4 (4): 18-58
YANG J. Web service componentization [J] Communications of the ACM, 2003, 46 (10): 35-40
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