A Cloud Computing Fault Detection Method Based on Deep Learning

ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.net/journal/jcc
E-mail: [email protected]

Citations

"A Cloud Computing Fault Detection Method Based on Deep Learning"
written by Weipeng Gao, Youchan Zhu,
published by Journal of Computer and Communications, Vol.5 No.12, 2017

has been cited by the following article(s):

[1]	Experiences with Deep Learning Enhanced Steering Mechanisms for Debugging of Fundamental Cloud Services
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[2]	Fault Detection for a One-Dimensional Wave PDE System
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[3]	Fault detection in GPU-enabled Cloud Systems–An Overview
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[4]	Fault Localization in Cloud using Centrality Measures
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[5]	Advanced Techniques to Predict and Detect Cloud System Failure: A Survey
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[7]	Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique
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[8]	Data analytics using statistical methods and machine learning: a case study of power transfer units
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[9]	Fault Diagnosis and Identification of Power Capacitor Based on Edge Cloud Computing and Deep Learning
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[10]	Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System
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[1]	Experiences With Deep Learning Enhanced Steering Mechanisms for Debugging of Fundamental Cloud Services IEEE Access, 2023 DOI:10.1109/ACCESS.2023.3243201

[2]	Fault detection in GPU-enabled Cloud Systems – An Overview 2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI), 2022 DOI:10.1109/SAMI54271.2022.9780804

[3]	Fault Localization in Cloud using Centrality Measures 2022 IEEE 29th Annual Software Technology Conference (STC), 2022 DOI:10.1109/STC55697.2022.00033

[4]	Advanced Techniques to Predict and Detect Cloud System Failure: A Survey 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022 DOI:10.1109/ICECA55336.2022.10009597

[5]	Data analytics using statistical methods and machine learning: a case study of power transfer units The International Journal of Advanced Manufacturing Technology, 2021 DOI:10.1007/s00170-021-06979-7

[6]	Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique Chaos, Solitons & Fractals, 2021 DOI:10.1016/j.chaos.2020.110592

[7]	Fault Diagnosis and Identification of Power Capacitor Based on Edge Cloud Computing and Deep Learning Mathematical Problems in Engineering, 2020 DOI:10.1155/2020/3120805

[8]	Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System Processes, 2019 DOI:10.3390/pr7030172