Xtricorder: a likelihood-enhanced self-rotation function and application to a machine learning-enhanced Matthews prediction of asymmetric unit copy number. [PDF]
McCoy AJ, Read RJ.
europepmc +1 more source
This study presents improvements to the non‐hydrostatic version of the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), enabling stable global simulations at 1.4‐km resolution. A systematic comparison with the hydrostatic version at resolutions from 9 to 1.4 km shows that non‐hydrostatic effects emerge in ...
Jozef Vivoda +3 more
wiley +1 more source
Higher-order regularity for a structurally damped plate equation on rough domains. [PDF]
Denk R, Roodenburg FB.
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
Temperature Dependence of a Thermosensitive Nanogel: A Dissipative Particle Dynamics Simulation of PNIPAM in Water. [PDF]
Valero D, Mas F, Madurga S.
europepmc +1 more source
ABSTRACT In this paper, we consider the optimal control problem for an unknown continuous‐time nonlinear system, and present a framework that integrates model‐based and model‐free methods to solve it. Each approach offers distinct advantages: model‐based techniques provide offline synthesis and data efficiency, while model‐free procedures excel at ...
Surabhi Athalye +2 more
wiley +1 more source
An Uncertainty-Aware Temporal Transformer for Probabilistic Interval Modeling in Wind Power Forecasting. [PDF]
Sun S +6 more
europepmc +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
Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi +3 more
wiley +1 more source

