Big Data in Earth system science and progress towards a digital twin
The concept of a digital twin of Earth envisages the convergence of Big Earth Data with
physics-based models in an interactive computational framework that enables monitoring …
physics-based models in an interactive computational framework that enables monitoring …
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …
AI-empowered next-generation multiscale climate modelling for mitigation and adaptation
Earth system models have been continously improved over the past decades, but systematic
errors compared with observations and uncertainties in climate projections remain. This is …
errors compared with observations and uncertainties in climate projections remain. This is …
[HTML][HTML] Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer …
Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past
decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of …
decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of …
Fourier neural operator for real-time simulation of 3D dynamic urban microclimate
Global urbanization has underscored the significance of urban microclimates for human
comfort, health, and building/urban energy efficiency. However, analyzing urban …
comfort, health, and building/urban energy efficiency. However, analyzing urban …
Land data assimilation: Harmonizing theory and data in land surface process studies
Data assimilation plays a dual role in advancing the “scientific” understanding and serving
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
An efficient digital twin based on machine learning SVD autoencoder and generalised latent assimilation for nuclear reactor physics
This paper proposes an approach that combines reduced-order models with machine
learning in order to create an digital twin to predict the power distribution over the core …
learning in order to create an digital twin to predict the power distribution over the core …
Deep generative data assimilation in multimodal setting
Robust integration of physical knowledge and data is key to improve computational
simulations such as Earth system models. Data assimilation is crucial for achieving this goal …
simulations such as Earth system models. Data assimilation is crucial for achieving this goal …
Digital twins in wind energy: Emerging technologies and industry-informed future directions
This article presents a comprehensive overview of the digital twin technology and its
capability levels, with a specific focus on its applications in the wind energy industry. It …
capability levels, with a specific focus on its applications in the wind energy industry. It …
A conceptual model of investment-risk prediction in the stock market using extreme value theory with machine learning: a semisystematic literature review
The COVID-19 pandemic has been an extraordinary event, the type of event that rarely
occurs but that has major impacts on the stock market. The pandemic has created high …
occurs but that has major impacts on the stock market. The pandemic has created high …