A Prediction Model of Ionospheric f o F 2 Based on Extreme Learning Machine-Reference-Cited by-同舟云学术

A Prediction Model of Ionospheric f o F 2 Based on Extreme Learning Machine

Published:2018-10 Issue:10 Volume:53 Page:1292-1301
ISSN:0048-6604
Container-title:Radio Science
language:en
Short-container-title:Radio Sci.

Author:

Bai Hongmei¹²³,Fu Haipeng¹³⁴^ORCID,Wang Jian¹⁴,Ma Kaixue¹³,Wu Taosuo¹³^ORCID,Ma Jianguo⁵

Affiliation:

1. School of Microelectronics; Tianjin University; Tianjin China

2. School of Mathematics and Statistics; Hulunbuir College; Hulunbuir China

3. Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology; Tianjin University; Tianjin China

4. Qingdao Key Laboratory of Ocean Perception and Information Transmission; Qingdao Institute for Ocean Technology of Tianjin University; Qingdao China

5. School of Computer; Guangdong University of Technology; Guangzhou China

Funder

Qingdao National Laboratory for Marine Science and Technology

Ministry of Science and Technology of the People's Republic of China

Tianjin Research Program of Application Foundation and Advanced Technology

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Electrical and Electronic Engineering,General Earth and Planetary Sciences,Condensed Matter Physics

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1029/2018RS006622/fullpdf

Reference29 articles.

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5. Characteristic of ionospheric foF2 and solar indices during the 23rd solar cycle over high latitude station, Syowa, Antarctica;Bhawre;American Journal of Climate Change,2015

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4. An Explainable Dynamic Prediction Method for Ionospheric foF2 Based on Machine Learning;Remote Sensing;2023-02-24

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