Machine Learning Techniques for Predicting Metamaterial Microwave Absorption Performance: A Comparison-Reference-Cited by-同舟云学术

Machine Learning Techniques for Predicting Metamaterial Microwave Absorption Performance: A Comparison

Published:2023 Issue: Volume:11 Page:128774-128783
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Jain Prince¹^ORCID,Chhabra Himanshu¹,Chauhan Urvashi²,Prakash Krishna³^ORCID,Samant Piyush⁴,Singh Dhiraj Kumar⁵,Soliman Mohamed S.⁶^ORCID,Islam Mohammad Tariqul⁷^ORCID

Affiliation:

1. Department of Mechatronics Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat, India

2. Department of Electronics and Communication Engineering, Parul University, Vadodara, Gujarat, India

3. Department of Electronics and Communication, NRI Institute of Technology, Vijayawada, Andhra Pradesh, India

4. Research and Development, Mirxes Laboratories Pvt. Ltd., Tukang Innovation Grove, Singapore

5. Kalpana Chawla Centre for Research in Space Science and Technology, Chandigarh University, Mohali, Punjab, India

6. Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia

7. Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

Funder

Ministry of Higher Education (MOHE), Malaysia, through the Fundamental Research Grant Scheme

Deanship of Scientific Research, Taif University, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10318092.pdf?arnumber=10318092

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5. Analysis of parameterization substrate thickness and permittivity for concentric split ring square reflectarray element;misran;Jurnal Kejuruteraan J Eng,2012

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