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Evolving Petri Nets for Situation Recognition
Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (SAIL)
Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (SAIL)
Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (SAIL)
2010 (engelsk)Inngår i: GEM 2010: Proceedings of the 2010 International Conference on Genetic and Evolutionary Methods / [ed] Hamid R. Arabnia, Ray R. Hashemi, Ashu M. G. Solo, CSREA Press, 2010, s. 29-35Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Situation recognition is an important problem to address for developing newcapabilities in the surveillance domain.  It is concerned with recognizing a priori defined situations of interest, which can be of concurrent and temporal nature, possibly occurring in a continuous flow of data and information. It is however a complex task to manually define what constitutes an interesting situation, and we therefore investigate the possibility of using genetic algorithms for evolving Petri nets for situation recognition. Our results show that: (1) it is possible to evolve complex Petri nets, (2) it is possible to increase the performance of manually  designed Petri nets, and (3) a dynamic genome representation consisting of  complex genes is beneficial compared to a representation consisting of bit strings.

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CSREA Press, 2010. s. 29-35
Emneord [en]
Evolving structure, genetic algorithms, genome representation, petri nets, situation recognition
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URN: urn:nbn:se:his:diva-4642ISBN: 1-60132-145-7 OAI: oai:DiVA.org:his-4642DiVA, id: diva2:392189
Konferanse
2010 International Conference on Genetic and Evolutionary Methods, GEM 2010, July 12-15, 2010, Las Vegas Nevada, USA
Tilgjengelig fra: 2011-01-26 Laget: 2011-01-26 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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