[1] S. D. Campbell, R. P. Jenkins, P. J. O'Connor, and D. Werner, The explosion of artificial intelligence in antennas and propagation: How deep learning is advancing our state of the art. IEEE Antennas and Propagation Magazine, 63(3), 16-27, 2021.

[2] Sumithra, P., and D. Thiripurasundari, Review on computational electromagnetics. Advanced Electromagnetics, 6(1), 42-55, 2017.

[3] F. Zardi, P. Nayeri, P. Rocca and R. Haupt, Artificial intelligence for adaptive and reconfigurable antenna arrays: A review. IEEE Antennas and Propagation Magazine, 63(3), 28-38, 2021.

[4] El Misilmani, Hilal M., Tarek Naous, and Salwa K. Al Khatib, A review on the design and optimization of antennas using machine learning algorithms and techniques. International Journal of RF and Microwave Computer‐Aided Engineering, 30(10), 10, 2020.

[5] A. B. Nassif, I. Shahin, I. Attili, M. Azzeh and K. Shaalan, Speech recognition using deep neural networks: a systematic review. IEEE Access, 7, 19143-19165, 2019.

[6] Wei-Tong Ding, Fei Meng, Yu-Bo Tian, Hui-Ning Yuan, Antenna optimization based on auto-context broad learning system. International Journal of Antennas and Propagation, Article ID 7338164, 10 pages, 2022.

[7] Ding, Wei-Tong, et al., Antenna optimization based on auto-context broad learning system. International Journal of Antennas and Propagation, 2022.

[8] S. Aslam, H. Herodotou, N. Ayub and S. M. Mohsin, deep learning based techniques to enhance the performance of microgrids: a review. International Conference on Frontiers of Information Technology (FIT), 116-1165, 2019.

[9] N. T. Tokan, F. Gunes, and Y. Tülay, Artificial neural design of microstrip antennas. Turkish Journal of Electrical Engineering & Computer Sciences, 14(3), 445-453, 2007.

[10] N. T. Tokan and F. Gunes, vector design of the microstrip antenna. IEEE 16th Signal Processing, Communication and Applications Conference, 1-4, 2008.

[11] Z. Zheng, X. Chen, and K. Huang, Application of support vector machines to the antenna design. International Journal of RF and Microwave Computer‐Aided Engineering, 21(1), 85-90, 2011.

[12] T. Khan and C.Roy, Prediction of slot‐position and slot‐size of a microstrip antenna using support vector regression. International Journal of RF and Microwave Computer‐Aided Engineering, 29(3), e21623, 2019.

[13] B. K. Singh, Design of rectangular microstrip patch antenna based on Artificial Neural Network algorithm. 2nd International Conference on Signal Processing and Integrated Networks (SPIN), 6-9, 2015.

[14] I. Vilovic and N. Burum, Design and feed position estimation for circular microstrip antenna based on neural network model. 6th European Conference on Antennas and Propagation (EUCAP), 3614-3617, 2012.

[15] P. Malathi and Raj Kumar, On the design of multilayer circular microstrip antenna using artificial neural networks. International Journal of Recent Ttrends in Engineering, 2(5), 70-74, 2009.

[16] A. Mishra, G. Janvale, B. V. Pawar and A. J. Patil, The design of circular microstrip patch antenna by using Conjugate Gradient algorithm of ANN. IEEE Applied Electromagnetics Conference (AEMC), 1-4, 2011.

[17] M. Pandit, Moumi and T Bose, Application of neural network model for designing circular monopole antenna. International Symposium on Devices MEMS. Intelligent Systems & Communication (ISDMISC)-Proceedings published by International Journal of Computer Applications (IJCA), 2011.

[18] V. Thakare, Vikas, and Pramod Kumar Singhal, Bandwidth analysis by introducing slots in microstrip antenna design using ANN. Progress In Electromagnetics Research M, 9, 107-122, 2009.

[19] Q. Wu, H. Wang and W. Hong, Broadband millimeter-wave siw cavity-backed slot antenna for 5G applications using machine-learning-assisted optimization method. International Workshop on Antenna Technology (iWAT), 9-12, 2019.

[20] L. Tenuti, G. Oliveri, D. Bresciani and A. Massa, Advanced learning-based approaches for reflectarrays design. 11th European Conference on Antennas and Propagation (EUCAP), 84-87, 2017.

[21] M. Salucci, L. Tenuti, G. Oliveri and A. Massa, Efficient prediction of the EM response of reflectarray antenna elements by an advanced statistical learning method. IEEE Transactions on Antennas and Propagation, 66(8), 3995-4007, 2018.

[22] S. Koziel, S. Ogurtsov and J. P. Jacobs, Low-cost design optimization of slot antennas using Bayesian support vector regression and space mapping. Loughborough Antennas & Propagation Conference (LAPC), 1-4, 2012.

[23] J. P. Jacobs, S. Koziel and S. Ogurtsov, Computationally efficient multi-fidelity bayesian support vector regression modeling of planar antenna input characteristics, IEEE Transactions on Antennas and Propagation, 61)2), 980-984, 2013.

[24] C. R. M. Silva and S. R. Martins, An adaptive evolutionary algorithm for uwb microstrip antennas optimization using a machine learning technique. Microwave and Optical Technology Letters, 55(8), 1864-1868, 2013.

[25] S. R. Martins, H. W. C. Lins, and C. R. M. Silva, A self-organizing genetic algorithm for UWB microstrip antenna optimization using a machine learning technique. International Conference on Intelligent Data Engineering and Automated Learning, Springer, Berlin, Heidelberg, 2012.

[26] B. Liu, H. Aliakbarian, Z. Ma, G. A. E. Vandenbosch, G. Gielen and P. Excell, An efficient method for antenna design optimization based on evolutionary computation and machine learning techniques. IEEE Transactions on Antennas And Propagation, 62(1), 7-18, 2013.

[27] [27] X. H. Chen, X. X. Guo, J. M. Pei and W. Y. Man, A hybrid algorithm of differential evolution and machine learning for electromagnetic structure optimization. 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC), 755-759, 2017.

[28] [28] S. K. Jain, Bandwidth enhancement of patch antennas using neural network dependent modified optimizer, International Journal of Microwave and Wireless Technologies, 8(7), 1111-1119, 2016.

[29] S. K. Jain, A. Patnaik, and S. N. Sinha, Design of custom-made stacked patch antennas: a machine learning approach. International Journal of Machine Learning and Cybernetics, 4(3), 189-194, 2013.

[30] Jain, S. K., A. Patnaik, and S. N. Sinha, Neural network based particle swarm optimizer for design of dual resonance X/Ku band stacked patch antenna. IEEE International Symposium on Antennas and Propagation (APSURSI). IEEE, 2011.

[31] A. Patnaik and S. N. Sinha, Design of custom-made fractal multi-band antennas using ANN-PSO [Antenna Designer's Notebook]. IEEE Antennas and Propagation Magazine, 53(4), 94-101, 2011.

[32] C. H. Wu and C. F. Lai, Data-driven diversity antenna selection for MIMO communication using machine learning. Journal of Internet Technology, 23(1),1-9, 2022.

[33] K. M. Faisal and W. Choi, Machine learning approaches for reconfigurable intelligent surfaces: a survey. IEEE Access, 10, 27343-27367, 2022.

[34] B. Sagir, E. Aydin, and H. Ilhan, Deep-learning assisted reconfigurable intelligent surfaces for cooperative communications. arXiv preprint arXiv:2201.10648, 2022.

[35] P. Nayeri, and R. L. Haupt, A testbed for adaptive beamforming with software defined radio arrays. 2016 IEEE/ACES International Conference on Wireless Information Technology and Systems (ICWITS) and Applied Computational Electromagnetics (ACES). IEEE, 2016.

[36] J. Brady, N. Behdad, and A. M. Sayeedx, Beamspace MIMO for millimeter-wave communications: System architecture, modeling, analysis, and measurements. IEEE Transactions on Antennas and Propagation, 61(7), 3814-3827, 2013.

[37] S. A. Mitilineos, S. C. A. Thomopoulos, and C. N. Capsalis, On array failure mitigation with respect to probability of failure, using constant excitation coefficients and a genetic algorithm. IEEE Antennas and Wireless Propagation Letters, 5, 187-190, 2006.

[38] H. -T. Chou and D. -Y. Cheng, Beam-pattern calibration in a realistic system of phased-array antennas via the implementation of a genetic algorithm with a measurement system. IEEE Transactions on Antennas and Propagation, 65(2), 593-601, 2016.

[39] Arnous, Reham, E. S. M. T. El-kenawy, and M. Saber. "A proposed routing protocol for mobile ad hoc networks." Int. J. Comput. Appl 975 (2019): 8887.

[40] Saber, Mohamed, and E. M. Elkenawy. "Design and implementation of accurate frequency estimator depend on deep learning." International Journal of Engineering & Technology 9, no. 2 (2020): 367-377.

[41] M Saber, Y Jitsumatsu, MTA Khan, A simple design to mitigate problems of conventional digital phase locked loop, Signal Processing: An international journal (SPIJ), 6(2), 65-77, 2012.

[42] Mohamed Saber, A novel design and Implementation of FBMC Transceiver for Low Power Applications. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 8(1), 83-93, 2020.

[43] A Elmitwally, M Elsaid, M Elgamal, Novel Multiagent-Based Scheme for Voltage Control Coordination in Smart Grids. Journal of Energy Engineering,141(3), 2014.

[44] A Elmitwally, M Elsaid, M Elgamal, Novel Multiagent-Based Scheme for Voltage Control Coordination in Smart Grids. Journal of Energy Engineering,141(3), 2014.

[45] [A. Elmitwally, M. Elsaid, M. Elgamal, Multi-agent-based voltage stabilization scheme considering load model effect. International Journal of Electrical Power & Energy Systems, 55, 225-237, 2014.

[46] Elsakaan, Asmaa A., et al., Economic Power Dispatch with Emission Constraint and Valve Point Loading Effect Using Moth Flame Optimization Algorithm. Advanced Engineering Forum, 28, 139-149, 2018.

[47] Ibrahim, Abdelhameed, and El-Sayed M. El-kenawy, Applications and datasets for superpixel techniques: A survey. Journal of Computer Science and Information Systems, 15(3), 1-6, 2020.

[48] El-kenawy, El-Sayed Towfek, Ali Ibraheem El-Desoky, and Amany M. Sarhan. A Bidder Behavior Learning Intelligent System for Trust Measurement. International Journal of Computer Applications, 89 (8), 2014.