Training Artificial Neural Network.

XOR Problem.

Summation Units, Log-Sigmoid Neurons with Biases.

Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons.

　　Returns mean square error between desired and actual outputs.

Reference Papers:

D. Karaboga, B. Basturk Akay, C. Ozturk, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS: Modeling Decisions for Artificial Intelligence, 4617/2007, 318-329, 2007.

D. Karaboga, C. Ozturk, Neural Networks Training by Artificial Bee Colony Algorithm on Pattern Classification, Neural Network World, 19(3), 279-292, 2009.

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-　Training Artificial Neural Network.

　XOR Problem.

　Summation Units, Log-Sigmoid Neurons with Biases.

　Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons.

　　Returns mean square error between desired and actual outputs.

　Reference Papers:

　D. Karaboga, B. Basturk Akay, C. Ozturk, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS: Modeling Decisions for Artificial Intelligence, 4617/2007, 318-329, 2007.

　D. Karaboga, C. Ozturk, Neural Networks Training by Artificial Bee Colony Algorithm on Pattern Classification, Neural Network World, 19(3), 279-292, 2009.

　*/