Machine Learning Based Inversion Method for 3-D Plasma Parameters-Reference-Cited by-同舟云学术

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Machine Learning Based Inversion Method for 3-D Plasma Parameters

Published:2023-11-10 Issue: Volume:27 Page:1-3
ISSN:
Container-title:2023 Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC)
language:
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Author:

Sun Xiaojun¹,Chen Wei²,Yang Lixia³

Affiliation:

1. Anhui University,Information Materials and Intelligent Sensing Laboratory of Anhui Province,Hefei,China

2. Advanced Laser Technology Laboratory of Anhui Province,Hefei,China

3. Anhui Province Key Laboratory of Target Recognition and Feature Extraction,Luan,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10426787/10426807/10426902.pdf?arnumber=10426902

Reference6 articles.

1. Resonance Frequency Inversion of Cold Unmagnetized Plasma Based on CDLT-FDTD and PSO Methods

2. Composite conducting-dielectric cylinder parameters reconstruction by means of SVM;Zhang;CHINESE JOURNAL OF RADIO SCIENCE,2012

3. Neural Network Model for Parameter Inversion in Electromagnetic Wave and Plasma Interaction Systems

4. JEC-FDTD for 2-D conducting cylinder coated by anisotropic magnetized plasma

5. Prediction of Hydration Heat of Mass Concrete Based on the SVR Model

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