Evolutionary viral-type algorithm for the inverse problem for iterated function systems

Authors:
Barbara Strug;Andrzej Bielecki;Marzena Bielecka
Affiliations:
Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Krakow, Poland;Institute of Computer Science, Jagiellonian University, Krakow, Poland;Department Geoinformatics and Applied Computer Science, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, Krakow, Poland
Venue:
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Year:
2007

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Abstract

In this article a possibility of enriching evolutionary algorithms by a specific type mechanism characteristic for replication of influenza viruses is discussed. Genetic material of influenza type A virus consists of eight separate segments. In some types of tasks such a structure of a genome can be more adequate than representation that consists of only one sequence. If influenza viruses strains infect the same cell then their RNA segments can mix freely producing progeny viruses. Furthermore, mistakes leading to new mutations are common. An evolutionary algorithm for solving the inverse problem for iterated function systems (IFSes) for a two-dimensional image is proposed. Four patterns are considered as examples and a preliminary statistical analysis results are also presented.