Integration of Particle Swarm Optimization (PSO) and Machine Learning to Improve Classification Accuracy During Antenna Design-Reference-Cited by-同舟云学术

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Integration of Particle Swarm Optimization (PSO) and Machine Learning to Improve Classification Accuracy During Antenna Design

Published:2023-05-11 Issue:3 Volume:24 Page:258-266
ISSN:1229-7607
Container-title:Transactions on Electrical and Electronic Materials
language:en
Short-container-title:Trans. Electr. Electron. Mater.

Author:

Singh Susheel Kumar,Kumar Mukesh,Singh Jeetendra^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

Link

https://link.springer.com/content/pdf/10.1007/s42341-023-00443-x.pdf

Reference35 articles.

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2. T. Khan, A. De, Modeling of microstrip antennas using neural networks techniques: A review. Int. J. RF Microw. Comput. Eng. 25(9), 747–757 (2015). https://doi.org/10.1002/mmce.2091

3. F. Doshi-Velez, B. Kim. Considerations for Evaluation and Generalization in Interpretable Machine Learning, pp. 3–17 (2018). https://doi.org/10.1007/978-3-319-98131-4_1.

4. S. Seyedzadeh, F.P. Rahimian, I. Glesk, M. Roper, Machine learning for estimation of building energy consumption and performance: a review. Vis. Eng. (2018). https://doi.org/10.1186/s40327-018-0064-7

5. O.M.K. Alhawi, J. Baldwin, A. Dehghantanha, Leveraging machine learning techniques for windows ransomware network traffic detection. Adv. Inf. Secur. 70, 93–106 (2018). https://doi.org/10.1007/978-3-319-73951-9_5

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