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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
Type: Journal paper
Language: English
View: 734

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Link to this Paper:
https://civilica.com/doc/542276

Document National Code:

JR_JACR-7-3_001

Index date: 1 January 2017

Multi-layer Perceptron Neural Network Training Based on Improved of Stud GA 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,

Multi-layer Perceptron Neural Network Training Based on Improved of Stud GA Keywords:

Genetic Algorithms , Chaos Theory , Artificial Neural Networks , Evolutionary , Neural Network , Stud GA

Multi-layer Perceptron Neural Network Training Based on Improved of Stud GA 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