Improvement of Multi-Layer Perceptron (MLP) training using optimization algorithms
نویسندگان
چکیده
Artificial Neural Network (ANN) is one of the modern computational methods proposed to solve increasingly complex problems in the real world (Xie et al., 2006 and Chau, 2007). ANN is characterized by its pattern of connections between the neurons (called its architecture), its method of determining the weights on the connections (called its training, or learning, algorithm), and its activation Function. Training is accomplished by presenting a sequence of training vectors, or patterns, each with an associated target output vector. Then, the weights are adjusted based on a learning algorithm.
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