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决策树企业信息系统故障自动诊断方法.pdf
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2021-01-24
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JIN Xin , YAN Longchuan, LIU Jun, ZHANG Shulin
State Grid Information & Telecommunication Branch, Beijing 100761, China
98+’)03’$ With the rapid growth of the scale and complexity of enterprise information systems, traditional fault
diagnosis and analysis methods relying on human experiences and manual operations cost more and more labor a nd
time. To solve this problem, an automatic algorithm was proposed. The algorithm exploits information from system
operation monitoring indicators and alarm data, based on decision tree, to automatica lly diagno se and analyze faults
of enterprise information systems. The a lgorithm was verified, and the decision tree mo del and training method was
simulated and analyzed comparatively under R language environment, using alarm da ta extracted from real operation
data of a typical large
-scale enterprise system. The experiment results show that this algorithm is able to achieve fast
automatic fault diagnosis accurately, and is much helpful on improving efficiencies of information system fault
processing.
:,1 ;")5+$ automatic diagnosis analysis, fault of information system, decision tree, R language
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