SHUFFLED FROG LEAPING ALGORITHM AND FEATURE SELECTION FOR IMPROVING RECOGNITION RATE OF PERSIAN HANDWRITTEN DIGITS CLASSIFIER

Najme Ghanbari; Mahdi Heidari

doi:10.15628/holos.2017.6144

Autores

Najme Ghanbari University of Zabol http://orcid.org/0000-0002-2804-1790
Mahdi Heidari University of Zabol http://orcid.org/0000-0002-9208-1252

DOI:

https://doi.org/10.15628/holos.2017.6144

Palavras-chave:

Persian handwritten digits recognition, Shuffled Frog Leaping algorithm (SFLA), features selection

Resumo

In this paper, Shuffled Frog Leaping Algorithm is used to improve the recognition rate of Persian handwritten digits. In proposed approach, the effective features in increasing the recognition rate are selected using the Binary Shuffled Frog Leaping Algorithm (BSFLA). By selecting the most suitable features from among all extracted features, the recognition rate is improved and computational costs are also decreased. The fitness function in BSFLA is the number of errors in the Fuzzy classifier which its minimum value is desired. The results indicate that Shuffled Frog Leaping algorithm (SFLA) is more efficient

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Biografia do Autor

Najme Ghanbari, University of Zabol

Department of Electrical Engineering

Mahdi Heidari, University of Zabol

Department of Electrical Engineering

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