Abstract:
In this work, a new strategy of neural networks (NN) is proposed to modeling
microwave waveguide structures (Pseudo-Elliptic filter, Broad-band E-plane filters and Hplane waveguide filters considering rounded corners). In order to enhance the capacities of
the NN, we trained NN by the hybrids algorithms based on combining between back
propagation (BP) algorithm and swarm intelligence algorithms (Social-Spider optimization
SSO, spider monkey optimization SMO and Teaching–Learning-Based Optimization
TLBO). To validate the training of neural networks using the proposed algorithms, we
compared the results of convergence and modeling obtained with the results obtained using
basic algorithms (SSO, SMO and TLBO) and also compared with population based
algorithm, which is widely used in training NN namely particle swarm optimization (PSO).
The results prove that the proposed hybrids algorithms have given better results.
