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Social-Spider Optimization Neural Networks for Microwave Filters Modeling

Abstract : In this paper, Social-Spider optimization (SSO) algorithm is proposed for training artificial neural networks (ANN). Further, the trained networks are tested on two microwave filters modeling (Broad-band E-plane filters with improved stop-band and H-plane waveguide filters considering rounded corners). To validate the effectiveness of this proposed strategy, we compared the results of convergence and modeling obtained with the results obtained by NN used a population based algorithm namely Particle Swarm Optimization (PSO-NN). The results prove that the proposed SSO-NN method has given better results.
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Submitted on : Tuesday, November 6, 2018 - 5:04:37 PM
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Erredir Chahrazad, Emir Bouarroudj, Mohamed Riabi. Social-Spider Optimization Neural Networks for Microwave Filters Modeling. 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA), May 2018, Oran, Algeria. pp.364-372, ⟨10.1007/978-3-319-89743-1_32⟩. ⟨hal-01913878⟩



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