%0 Conference Proceedings
%T Social-Spider Optimization Neural Networks for Microwave Filters Modeling
%+ Laboratoire d'Electromagnétisme et Télécommunication (LET)
%A Chahrazad, Erredir
%A Bouarroudj, Emir
%A Riabi, Mohamed, Lahdi
%Z Part 4: Optimization
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA)
%C Oran, Algeria
%Y Abdelmalek Amine
%Y Malek Mouhoub
%Y Otmane Ait Mohamed
%Y Bachir Djebbar
%I Springer International Publishing
%3 Computational Intelligence and Its Applications
%V AICT-522
%P 364-372
%8 2018-05-08
%D 2018
%R 10.1007/978-3-319-89743-1_32
%K Neural networks
%K Social-Spider optimization
%K Microwave structures
%K Modeling
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 5
%2 https://inria.hal.science/hal-01913878/document
%2 https://inria.hal.science/hal-01913878/file/467079_1_En_32_Chapter.pdf
%L hal-01913878
%U https://inria.hal.science/hal-01913878
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-CIIA
%~ IFIP-AICT-522