Image-based time series forecasting: A deep convolutional neural network approach
Inspired by the successful use of deep learning in computer vision, in this paper we
introduce ForCNN, a novel deep learning method for univariate time series forecasting that …
introduce ForCNN, a novel deep learning method for univariate time series forecasting that …
[HTML][HTML] Machine learning in orbit estimation: A survey
Since the late 1950s, when the first artificial satellite was launched, the number of Resident
Space Objects has steadily increased. It is estimated that around one million objects larger …
Space Objects has steadily increased. It is estimated that around one million objects larger …
Predict water quality using an improved deep learning method based on spatiotemporal feature correlated: a case study of the Tanghe Reservoir in China
The ecological health of water quality is an essential factor in the survival and development
of human beings. By setting up multiple sensors in the water body, people observe the …
of human beings. By setting up multiple sensors in the water body, people observe the …
F10.7 Daily Forecast Using LSTM Combined With VMD Method
Y Hao, J Lu, G Peng, M Wang, J Li, G Wei - Space Weather, 2024 - Wiley Online Library
The F10. 7 solar radiation flux is a well‐known parameter that is closely linked to solar
activity, serving as a key index for measuring the level of solar activity. In this study, the …
activity, serving as a key index for measuring the level of solar activity. In this study, the …
[HTML][HTML] Benchmarking deep learning approaches for all-vs-all conjunction screening
E Stevenson, V Rodriguez-Fernandez… - Advances in Space …, 2023 - Elsevier
The all-vs-all problem, for which conjunctions are screened for over all possible sets of
catalogued objects, is crucial for space traffic management and space situational …
catalogued objects, is crucial for space traffic management and space situational …
Probabilistic solar proxy forecasting with neural network ensembles
JD Daniell, PM Mehta - Space Weather, 2023 - Wiley Online Library
Abstract Space weather indices are used commonly to drive forecasts of thermosphere
density, which affects objects in low‐Earth orbit (LEO) through atmospheric drag. One …
density, which affects objects in low‐Earth orbit (LEO) through atmospheric drag. One …
On Generalized Additive Models for representation of solar EUV irradiance
In the context of space weather forecasting, solar EUV irradiance specification is needed on
multiple time scales, with associated uncertainty quantification for determining the accuracy …
multiple time scales, with associated uncertainty quantification for determining the accuracy …
A novel learning approach for short-term photovoltaic power forecasting-A review and case studies
K Ferkous, M Guermoui, S Menakh, A Bellaour… - … Applications of Artificial …, 2024 - Elsevier
Integrating photovoltaic power into the power system can offer significant economic and
environmental benefits. However, the intermittent and random nature of photovoltaic power …
environmental benefits. However, the intermittent and random nature of photovoltaic power …
Forecasting medium-term F10. 7 using the deep-learning informer model
K Zhang, P Zuo, Z Zou, X Feng, Y Huang, S Wang… - Solar Physics, 2024 - Springer
Abstract The daily 10.7-cm solar radio flux (F10. 7) is one of the most important solar activity
indices and has been widely applied in various space environment modeling as a crucial …
indices and has been widely applied in various space environment modeling as a crucial …
Very short-term solar ultraviolet-A radiation forecasting system with cloud cover images and a Bayesian optimized interpretable artificial intelligence model
High-dose single exposures of long-wavelength ultraviolet-A (UV-A) radiation may trigger
severe biological and skin tissue damage in humans and animals, as well as photosynthetic …
severe biological and skin tissue damage in humans and animals, as well as photosynthetic …