Optimal Parameter Selection for Unsupervised Neural Network Using Genetic Algorithm
نویسندگان
چکیده
منابع مشابه
Optimal parameter selection for unsupervised neural network using genetic algorithm
K-means Fast Learning Artificial Neural Network (K-FLANN) is an unsupervised neural network requires two parameters: tolerance and vigilance. Best Clustering results are feasible only by finest parameters specified to the neural network. Selecting optimal values for these parameters is a major problem. To solve this issue, Genetic Algorithm (GA) is used to determine optimal parameters of K-FLAN...
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ژورنال
عنوان ژورنال: International Journal of Computer Science, Engineering and Applications
سال: 2013
ISSN: 2231-0088,2230-9616
DOI: 10.5121/ijcsea.2013.3502