NDLI: Description of Key Performance Index States based on Cloud Theory and Weight Mean method for Multi-sensor

Content Provider	IEEE Xplore Digital Library
Author	Qiuyu Zhang Lei Sun Yanfeng Jin
Copyright Year	2007
Description	Author affiliation: Lanzhou Univ. of Technol., Lanzhou (Qiuyu Zhang; Lei Sun; Yanfeng Jin)
Abstract	Key performance index analysis is a good complementing to the evaluation of past system security states, and the study on it has realistic meanings accordingly. It is realized that cloud theory and the weighted mean method for multi-sensor could qualitatively describe key performance index states. The data gathered from the multi-sensor under normal states will be tested for consistency by using distributing graph method firstly and will come out the fusion of the minimum average mean variance value by using the weighted mean method for multi-sensor secondly. Then the above data fusion will be compared with the key performance index data at every arbitrary moment and each amount of deviation by forgoing compare will be gained. At last the five remark sets constructed from cloud theory combining with the amount of deviation will realize the qualitative description of key performance index states. The experiment result shows the validity of this method.
Starting Page	350
Ending Page	354
File Size	2939626
Page Count	5
File Format	PDF
ISBN	9780769529097
DOI	10.1109/SNPD.2007.73
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clouds Data security Educational institutions Computer networks Performance analysis Distributed computing Artificial intelligence Sun Testing Software engineering
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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