Soft Fault Detection Algorithms for Multi-Parallel Data Streams Under the Cloud Computing

In the fault detection of multi-parallel data streams, the error probability of traditional methods is large, which cannot effectively meet the soft fault detection for multi-parallel data stream, causing the problem of low detection efficiency. A soft fault detection algorithm based on adaptive mul...

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Vydáno v:Journal of advanced computational intelligence and intelligent informatics Ročník 22; číslo 7; s. 1114 - 1119
Hlavní autor: Meng, Hongbing
Médium: Journal Article
Jazyk:angličtina
Vydáno: 20.11.2018
ISSN:1343-0130, 1883-8014
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Abstract In the fault detection of multi-parallel data streams, the error probability of traditional methods is large, which cannot effectively meet the soft fault detection for multi-parallel data stream, causing the problem of low detection efficiency. A soft fault detection algorithm based on adaptive multi-parallel data stream is proposed. The soft fault feature in the data stream is extracted, and the adaptive soft fault detection algorithm is used to detect the fault of the multi-parallel data stream, which can overcome the disadvantages of traditional methods, effectively improve the efficiency, safety and the accuracy. Experimental results showed that the proposed method can effectively improve the efficiency of fault detection.
AbstractList In the fault detection of multi-parallel data streams, the error probability of traditional methods is large, which cannot effectively meet the soft fault detection for multi-parallel data stream, causing the problem of low detection efficiency. A soft fault detection algorithm based on adaptive multi-parallel data stream is proposed. The soft fault feature in the data stream is extracted, and the adaptive soft fault detection algorithm is used to detect the fault of the multi-parallel data stream, which can overcome the disadvantages of traditional methods, effectively improve the efficiency, safety and the accuracy. Experimental results showed that the proposed method can effectively improve the efficiency of fault detection.
Author Meng, Hongbing
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10.1109/TPWRD.2017.2680456
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10.20965/jaciii.2016.p0324
10.1007/s11042-015-2649-7
10.1109/TIE.2016.2515057
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CorporateAuthor College of Information Engineering, Tarim University Alar, Xinjiang 843300, China
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