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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/12844

Title: Diagnosis of Stochastic Discrete Event Systems Based on N-gram Models
Authors: Yoshimoto, Miwa
Kobayashi, Koichi
Hiraishi, Kunihiko
Keywords: stochastic discrete event systems
N-gram models
Issue Date: 2015-02-01
Publisher: 電子情報通信学会
Magazine name: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume: E98-A
Number: 2
Start page: 618
End page: 625
DOI: 10.1587/transfun.E98.A.618
Abstract: In this paper, we present a new method for diagnosis of stochastic discrete event system. The method is based on anomaly detection for sequences. We call the method sequence profiling (SP). SP does not require any system models and any system-specific knowledge. The only information necessary for SP is event logs from the target system. Using event logs from the system in the normal situation, N-gram models are learned, where the N-gram model is used as approximation of the system behavior. Based on the N-gram model, the diagnoser estimates what kind of faults has occurred in the system, or may conclude that no faults occurs. Effectiveness of the proposed method is demonstrated by application to diagnosis of a multi-processor system.
Rights: Copyright (C)2015 IEICE. Miwa Yoshimoto, Koichi Kobayashi, Kunihiko Hiraishi, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E98-A(2), 2015, 618-625. http://www.ieice.org/jpn/trans_online/
URI: http://hdl.handle.net/10119/12844
Material Type: publisher
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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