Description of key performance index states based on cloud theory and weighted mean method for multi-sensor

Zhang Qiuyu, Sun Lei, Jin Yanfeng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings - SNPD 2007
Subtitle of host publicationEighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Pages350-354
Number of pages5
DOIs
StatePublished - 2007
Externally publishedYes
EventSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Qingdao, China
Duration: 30 Jul 20071 Aug 2007

Publication series

NameProceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Volume1

Conference

ConferenceSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Country/TerritoryChina
CityQingdao
Period30/07/071/08/07

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