[HTML][HTML] Artificial intelligence models for refrigeration, air conditioning and heat pump systems
DS Adelekan, OS Ohunakin, BS Paul - Energy Reports, 2022 - Elsevier
Artificial intelligence (AI) models for refrigeration, heat pumps, and air conditioners have
emerged in recent decades. The universal approximation accuracy and prediction …
emerged in recent decades. The universal approximation accuracy and prediction …
A survey of uncertainty quantification in machine learning for space weather prediction
With the availability of data and computational technologies in the modern world, machine
learning (ML) has emerged as a preferred methodology for data analysis and prediction …
learning (ML) has emerged as a preferred methodology for data analysis and prediction …
The challenge of machine learning in space weather: Nowcasting and forecasting
E Camporeale - Space weather, 2019 - Wiley Online Library
The numerous recent breakthroughs in machine learning make imperative to carefully
ponder how the scientific community can benefit from a technology that, although not …
ponder how the scientific community can benefit from a technology that, although not …
Ensemble machine learning of random forest, AdaBoost and XGBoost for vertical total electron content forecasting
Space weather describes varying conditions between the Sun and Earth that can degrade
Global Navigation Satellite Systems (GNSS) operations. Thus, these effects should be …
Global Navigation Satellite Systems (GNSS) operations. Thus, these effects should be …
Solar wind—Magnetosphere coupling functions: Pitfalls, limitations, and applications
M Lockwood - Space weather, 2022 - Wiley Online Library
Solar wind‐magnetosphere coupling functions have now been in use for almost 50 years. In
that time, a very large number of formulations have been proposed. As they become …
that time, a very large number of formulations have been proposed. As they become …
Group sunspot numbers: a new reconstruction of sunspot activity variations from historical sunspot records using algorithms from machine learning
Historical sunspot records and the construction of a comprehensive database are among the
most sought after research activities in solar physics. Here, we revisit the issues and …
most sought after research activities in solar physics. Here, we revisit the issues and …
Is our understanding of solar-wind/magnetosphere coupling satisfactory?
JE Borovsky - Frontiers in Astronomy and Space Sciences, 2021 - frontiersin.org
An assessment of our physics-based understanding of solar-wind/magnetosphere coupling
finds that the understanding is not complete. Solar-wind/magnetosphere coupling is …
finds that the understanding is not complete. Solar-wind/magnetosphere coupling is …
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 …
Symplectic learning for Hamiltonian neural networks
Abstract Machine learning methods are widely used in the natural sciences to model and
predict physical systems from observation data. Yet, they are often used as poorly …
predict physical systems from observation data. Yet, they are often used as poorly …
Classifying the magnetosheath behind the quasi‐parallel and quasi‐perpendicular bow shock by local measurements
T Karlsson, S Raptis, H Trollvik… - Journal of Geophysical …, 2021 - Wiley Online Library
We investigate and evaluate the possibility of using local magnetosheath measurements to
classify the plasma according to upstream conditions. In order to do this, we use …
classify the plasma according to upstream conditions. In order to do this, we use …