Multi-layer Perceptron Neural Network Training Based on Improved of Stud GA
Publish place: Journal of Advances in Computer Research، Vol: 7، Issue: 3
Publish Year: 1395
نوع سند: مقاله ژورنالی
زبان: English
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JR_JACR-7-3_001
تاریخ نمایه سازی: 12 دی 1395
Abstract:
Neural network is one of the most widely used algorithms in the field of machine learning, On the other hand, neural network training is a complicated and important process. Supervised learning needs to be organized to reach the goal as soon as possible. A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. Hence, in this paper,
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Authors
Firozeh Razavi
Department of Management and Economics, Science and Research Branch, Islamic Azad University Tehran, Iran
Faramarz Zabihi
Department of Computer Engineering, Sari branch, Islamic Azad University, Sari, Iran
Mirsaeid Hosseini Shirvani
Department of Computer Engineering, Sari branch, Islamic Azad University, Sari, Iran