Machine learning regression models for prediction of multiple ionospheric parameters
The variation of the ionospheric parameters has a crucial role in space weather,
communication, and navigation applications. In this research, we analyze the prediction …
communication, and navigation applications. In this research, we analyze the prediction …
Ionospheric TEC prediction using hybrid method based on ensemble empirical mode decomposition (EEMD) and long short-term memory (LSTM) deep learning …
Total electron data (TEC) from GPS nowadays can be used as a tool for understanding the
space weather phenomena. The development of prediction model for TEC is quiet crucial …
space weather phenomena. The development of prediction model for TEC is quiet crucial …
Ionosphere Variability II: Advances in theory and modeling
I Tsagouri, DR Themens, A Belehaki, JS Shim… - Advances in Space …, 2023 - Elsevier
This paper aims to provide an overview on recent advances in ionospheric modeling
capabilities, with the emphasis in the efforts relevant to electron density variability. The …
capabilities, with the emphasis in the efforts relevant to electron density variability. The …
An Artificial Neural Network‐Based Ionospheric Model to Predict NmF2 and hmF2 Using Long‐Term Data Set of FORMOSAT‐3/COSMIC Radio Occultation …
V Sai Gowtam, S Tulasi Ram - Journal of Geophysical …, 2017 - Wiley Online Library
Abstract Artificial Neural Networks (ANNs) are known to be capable of solving linear as well
as highly nonlinear problems. Using the long‐term and high‐quality data set of Formosa …
as highly nonlinear problems. Using the long‐term and high‐quality data set of Formosa …
Potential of Regional Ionosphere Prediction Using a Long Short‐Term Memory Deep‐Learning Algorithm Specialized for Geomagnetic Storm Period
JH Kim, YS Kwak, YH Kim, SI Moon, SH Jeong… - Space …, 2021 - Wiley Online Library
In our previous study (Moon et al., 2020, https://doi. org/10.3938/jkps. 77.1265), we
developed a long short‐term memory (LSTM) deep‐learning model for geomagnetic quiet …
developed a long short‐term memory (LSTM) deep‐learning model for geomagnetic quiet …
A combination prediction model of long-term ionospheric foF2 based on entropy weight method
H Bai, F Feng, J Wang, T Wu - Entropy, 2020 - mdpi.com
It is critically meaningful to accurately predict the ionospheric F2 layer critical frequency
(foF2), which greatly limits the efficiency of communications, radar, and navigation systems …
(foF2), which greatly limits the efficiency of communications, radar, and navigation systems …
A bidirectional long short-term memory-based ionospheric foF2 and hmF2 models for a single station in the low latitude region
Equatorial electrojet (EEJ) and the subsequent development of equatorial ionization
anomaly (EIA) are responsible for the highly complex and nonlinear variability nature of the …
anomaly (EIA) are responsible for the highly complex and nonlinear variability nature of the …
Advanced machine learning optimized by the genetic algorithm in ionospheric models using long-term multi-instrument observations
The ionospheric delay is of paramount importance to radio communication, satellite
navigation and positioning. It is necessary to predict high-accuracy ionospheric peak …
navigation and positioning. It is necessary to predict high-accuracy ionospheric peak …
A new artificial neural network‐based global three‐dimensional ionospheric model (ANNIM‐3D) using long‐term ionospheric observations: Preliminary results
VS Gowtam, S Tulasi Ram, B Reinisch… - Journal of …, 2019 - Wiley Online Library
In this paper, we present the preliminary results of a new global three‐dimensional (3‐D)
ionospheric model developed using artificial neural networks (ANNs) by assimilating long …
ionospheric model developed using artificial neural networks (ANNs) by assimilating long …
Application of a multi‐layer artificial neural network in a 3‐D global electron density model using the long‐term observations of COSMIC, Fengyun‐3C, and Digisonde
The ionosphere plays an important role in satellite navigation, radio communication, and
space weather prediction. However, it is still a challenging mission to develop a model with …
space weather prediction. However, it is still a challenging mission to develop a model with …