A pilot variational coupled reanalysis based on the CESAM climate model
Variational data assimilation of in‐situ and satellite ocean data and reanalysis atmospheric data into an intermediate complexity Earth system model is possible by adjusting the surface fluxes and internal model parameters. This pilot application requires nearly complete information on the atmospheric state for synchronization.
Armin Köhl +6 more
wiley +1 more source
Optimization of mine ventilation energy consumption based on improved dung beetle algorithm. [PDF]
Bingyan G, Zhe K.
europepmc +1 more source
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley +1 more source
We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie +3 more
wiley +1 more source
Axes Mapping and Sensor Fusion for Attitude-Unconstrained Pedestrian Dead Reckoning. [PDF]
Isaia C, Yu L, Cai W, Michaelides MP.
europepmc +1 more source
Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim +3 more
wiley +1 more source
Measured‐State Conditioned Recursive Feasibility for Stochastic Model Predictive Control
ABSTRACT In this paper, we address the problem of designing stochastic model predictive control (SMPC) schemes for linear systems affected by unbounded disturbances. The contribution of the paper is rooted in a measured‐state initialization strategy. First, due to the nonzero probability of violating chance‐constraints in the case of unbounded noise ...
Mirko Fiacchini +2 more
wiley +1 more source
Hybrid aerodynamic and structural optimization of super-tall buildings under wind loads for sustainable and cost-efficient design. [PDF]
Al-Masoodi AHH +2 more
europepmc +1 more source
The role of identification in data‐driven policy iteration: A system theoretic study
Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley +1 more source
A versatile large-scale coherent Ising machine from microwave to visible and telecom wavelength bands. [PDF]
Zhang H, Li J, Zhu H.
europepmc +1 more source

