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Genetic Matrix Algorithm; Simultaneous Optimization of Structure and Numerical Parameters
Author(s) -
Fujishima Wataru,
Nagao Tomoharu
Publication year - 2008
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20238
Subject(s) - algorithm , computer science , genetic algorithm , matrix (chemical analysis) , numerical analysis , mathematical optimization , mathematics , machine learning , materials science , composite material , mathematical analysis
Genetic Algorithm is often used to optimize numerical parameters, and Genetic Programming is used to optimize structure. However, optimizing both structure and numerical parameters simultaneously is quite difficult. Many different algorithms have been developed with the goal of optimizing both structure and numerical parameters simultaneously. However, those algorithms are not satisfactory in the sight of simultaneous optimization. We developed a new algorithm named Genetic Matrix Algorithm (GMA), which can evolve structure and numerical parameters simultaneously. The new algorithm, GMA, can evolve tree‐structured programs, which include numerical parameters in each of the nonterminal nodes. In this paper, we apply GMA to evolve image processing algorithms. Experimental results show that we can construct new useful image processing algorithms, which cannot be constructed using only fixed thresholds. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.