Abstract
A data-driven cloud test fault diagnosis method is proposed for the current testing system based on cloud computing, which has a low utilization rate of test data and fails to give full play to the operation and storage capacity of cloud computing. Firstly, the initial fuzzy reasoning fault diagnosis method is constructed based on expert knowledge and system parameters. Secondly, GSA is used to optimize the model based on historical data. Finally, the simulation platform is used for experimental verification. The results show that the system can effectively improve the utilization rate of cloud test data and achieve more accurate fault diagnosis.
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Kang, W., Xiao, J., Kong, X. (2020). Research on Data-Driven Fault Diagnosis Technology of Cloud Test. In: Jain, V., Patnaik, S., Popențiu Vlădicescu, F., Sethi, I. (eds) Recent Trends in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-9406-5_28
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DOI: https://doi.org/10.1007/978-981-13-9406-5_28
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