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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)
A Novel Anomaly Detection Algorithm Based on Real-Valued Negative Selection System
Adelaide, Australia
January 23-January 24
ISBN: 0-7695-3090-7
In this paper, a new method of detector generation and matching mechanism for Negative Selection Algorithm(NSA )is introduced with variable properties, which are called the Nsa-Vs-Detector. The detectors can be variable in different ways using this concept, the paper describes an algorithm when the variable parameter is the size of the detectors in real-valued space. The algorithm is tested with a synthetic datasets, the new method improves the NSA's efficiency and reliability without significant increase in complexity.
Citation:
Hu Zhengbing, Zhou Ji, Ma Ping, "A Novel Anomaly Detection Algorithm Based on Real-Valued Negative Selection System," wkdd, pp.499-502, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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