Research Article
Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Pseudocode 1
Pseudocode of CSERN algorithm.
() Initializes CS population size dimension and ERN structure | () Load the training data | () While MSE < stopping criteria | () Pass the Cuckoo nests as weights to network | () Feed forward network runs using the weights initialized with CS | () Calculate the error using (7) | () Minimize the error by adjusting network parameter using CS | () Generate Cuckoo egg () by taking Levy flight from random nest | | () Abandon a fraction of the worst nest. Build new nest at new location via Levy flight to replace the old one | () Evaluate the fitness of the nest, Chose a random nest | If | (a) Then | (b) | (c) | End if | () CS keeps on calculating the best possible weight at each epoch until the network is converged. | End While |
|