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Détail de l'auteur
Auteur Jia-Cen Fang
Documents disponibles écrits par cet auteur
Affiner la rechercheLearning intelligent genetic algorithms using japanese nonograms / Tsai, Jinn-Tsong in IEEE transactions on education, Vol. 55 N° 2 (Mai 2012)
[article]
in IEEE transactions on education > Vol. 55 N° 2 (Mai 2012) . - pp. 164 - 168
Titre : Learning intelligent genetic algorithms using japanese nonograms Type de document : texte imprimé Auteurs : Tsai, Jinn-Tsong, Auteur ; Ping-Yi Chou, Auteur ; Jia-Cen Fang, Auteur Année de publication : 2013 Article en page(s) : pp. 164 - 168 Note générale : Education Langues : Anglais (eng) Mots-clés : Condensed encoding Japanese nonograms Genetic algorithms (GAs) Pedagogical issues Teaching sequence Résumé : An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and mutation. In this paper, the condensed encoding ensures that the chromosome is a feasible solution in all rows for Japanese nonograms. In the reconstruction process of a Japanese nonogram, the numbers in the left column are used as encoding conditions, and the numbers in the top row with the improved fitness function are employed to evaluate the reconstruction result. From the computational experiments, the proposed IGA approach is applied to solve Japanese nonograms effectively, with better results than using a CGA. The students of the Department of Computer Science, National Pingtung University of Education, Taiwan, have gained practical experience of applying evolutionary algorithms to solve Japanese nonograms using both the proposed IGA and a CGA. The students learn that the IGA can find the right solution of the puzzle effectively, but the CGA cannot. ISSN : 0018-9359 En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5875911&sortType%3Das [...] [article] Learning intelligent genetic algorithms using japanese nonograms [texte imprimé] / Tsai, Jinn-Tsong, Auteur ; Ping-Yi Chou, Auteur ; Jia-Cen Fang, Auteur . - 2013 . - pp. 164 - 168.
Education
Langues : Anglais (eng)
in IEEE transactions on education > Vol. 55 N° 2 (Mai 2012) . - pp. 164 - 168
Mots-clés : Condensed encoding Japanese nonograms Genetic algorithms (GAs) Pedagogical issues Teaching sequence Résumé : An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and mutation. In this paper, the condensed encoding ensures that the chromosome is a feasible solution in all rows for Japanese nonograms. In the reconstruction process of a Japanese nonogram, the numbers in the left column are used as encoding conditions, and the numbers in the top row with the improved fitness function are employed to evaluate the reconstruction result. From the computational experiments, the proposed IGA approach is applied to solve Japanese nonograms effectively, with better results than using a CGA. The students of the Department of Computer Science, National Pingtung University of Education, Taiwan, have gained practical experience of applying evolutionary algorithms to solve Japanese nonograms using both the proposed IGA and a CGA. The students learn that the IGA can find the right solution of the puzzle effectively, but the CGA cannot. ISSN : 0018-9359 En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5875911&sortType%3Das [...]