Improving the accuracy of gradient descent back propagation algorithm (GDAM) on classification problems
The traditional Back-propagation Neural Network (BPNN) Algorithm is widely used in solving many real time problems in world. But BPNN possesses a problems in world. But BPNN possesses a problem of slow convergence and convergence to local minima. Previously, several modifications are suggested to im...
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| Capaian Atas Talian: | http://eprints.uthm.edu.my/2965/ |
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