• Chahrazad Erredir
  • Mohamed Lahdi Riabi
  • Halima Ammari
  • Emir Bouarroudj



Improved neural networks, modeling, teaching–learningbased optimization, waveguide filters


In this paper, Improved neural networks (INN) strategy is proposed to design two waveguide filters (Pseudo-elliptic waveguide filter and Broad-band e-plane filters with improved stop-band). The INN based in the efficient optimization method called teaching–learning-based optimization (TLBO). For validate effectiveness of this proposed strategy, we compared the results of convergence and modeling obtained with a population based algorithm which is widely used in training NN namely  Particle Swarm Optimization  (PSO-NN).  The results prove that the proposed INN has given better results.


[1] S.M. Ali, N.K. Nikolova, and M.H. Bakr, “Sensitivity Analysis with Full-Wave Electromagnetic Solvers Based on
Structured Grids,” IEEE Transactions on Magnetics, vol.40 ,pp.1521–1529, 2004.
[2] Y. Wang, M. Yu, H. Kabir, and Q.J. Zhang, “Application of Neural Networks in Space Mapping Optimization of
Microwave Filters,” International Journal of RF and Microwave Computer Aided Engineering, vol. 22, pp. 159–166,
[3] J. S. Sivia, A. P. S. Pharwaha, and T. S. Kamal, “Analysis and Design of Circular Fractal Antenna Using Artificial
Neural Networks,” Progress in Electromagnetics Research B, vol. 56, pp. 251– 267, 2013.
[4] A. A. Deshmukh, S.D. Kulkarni, A.P.C. Venkata, and N.V. Phatak, “Artificial Neural Network Model for Suspended
Rectangular Microstrip Antennas,” Procedia Computer Science, vol. 49, pp. 332–339, 2015
[5] D.J. Jwo, and K.P. Chin, “ Applying Back-propagation Neural Networks to GDOP Approximation,” The Journal of
Navigation, vol. 55, pp. 97–108, 2002.
[6] D. Gyanesh, K. P. Prasant, and K. P. Sasmita, “Artificial Neural Network Trained by Particle Swarm Optimization for
Non-Linear Channel Equalization,” Expert Systems with Applications, vol. 41, pp. 3491–3496, 2014.
[7] S. Ding, Y. Zhang, J. Chen, and J. Weikuan, “Research on Using Genetic Algorithms to Optimize Elman Neural
Networks,” Neural Computing and Applications, vol.23, pp. 293–297, 2013.
[8] K. Khan, and A. Sahai, “A Comparison of BA, GA, PSO, BP and LM for Training Feed Forward Neural Networks in ELearning Context,” International Journal of Intelligent Systems and Applications, vol.4, pp. 23 – 29, 2012.
[9] R. V. Rao, V. Patel , “An improved teaching-learning-based optimization algorithm for solving unconstrained
optimization problems,” Scientia Iranica ,vol 20, pp. 710–720, 2014.
[10] R.V. Rao, V. J. Savsani, and D. P. Vakharia, “Teaching–Learning-Based Optimization: A Novel Method for
Constrained Mechanical Design Optimization Problems,” Computer-Aided Design, vol.43, pp. 303–315, 2011.
[11] R.V. Rao, V. J. Savsani, and D. P. Vakharia, “Teaching–Learning-Based Optimization: An Optimization Method for
Continuous Non-Linear Large Scale Problems,” Information Sciences, vol.183, pp. 1–15, 2012.
[12] R. V. Rao , D. P. Rai, “Optimization of fused deposition modeling process using teaching-learning-based optimization
algorithm,” Engineering Science and Technology, an International Journal , 19, pp. 587–603, 2016.
[13] Q. Zhang, and Y. Lu, “Design of Wide-Band Pseudo-Elliptic Waveguide Filters with Cavity-Backed Inverters,”IEEE
Microwave And Wireless Components Letters, vol.20 ,pp. 604–606, 2010.
[14] X. Zhengbin, G. Jian , Q. Cheng, and D. Wenbin D, “Broad-Band E-plane filters with improved stop-band
performance,” IEEE Microwave and Wireless Components Letters , vol. 21,pp. 350–352, 2011.




How to Cite

Chahrazad Erredir, Mohamed Lahdi Riabi, Halima Ammari, & Emir Bouarroudj. (2017). DESIGN OF WAVEGUIDE STRUCTURES USING IMPROVED NEURAL NETWORKS. Journal of Microwaves, Optoelectronics and Electromagnetic Applications (JMOe), 16(4), 900–907.



Regular Papers