Real-valued negative selection algorithm with a Quasi-Monte Carlo genetic detector generation

Authors:
Jorge L. M. Amaral;José F. M. Amaral;Ricardo Tanscheit
Affiliations:
Dept. of Electronics and Telecommunications Engineering, Rio de Janeiro State University, Rio de Janeiro, RJ, Brazil;Dept. of Electronics and Telecommunications Engineering, Rio de Janeiro State University, Rio de Janeiro, RJ, Brazil;Dept. of Electrical Engineering, Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
Venue:
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Year:
2007

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Abstract

A new scheme for detector generation for the Real-Valued Negative Selection Algorithm (RNSA) is presented. The proposed method makes use of genetic algorithms and Quasi-Monte Carlo Integration to automatically generate a small number of very efficient detectors. Results have demonstrated that a fault detection system with detectors generated by the proposed scheme is able to detect faults in analog circuits and in a ball bearing dataset.