Zobrazeno 1 - 10
of 3 556
pro vyhledávání: '"Romero, Juan A."'
Autor:
Campoy-Nieves, Alejandro, Manjavacas, Antonio, Jiménez-Raboso, Javier, Molina-Solana, Miguel, Gómez-Romero, Juan
Publikováno v:
Energy and Buildings, 115075 (2024)
Simulation has become a crucial tool for Building Energy Optimization (BEO) as it enables the evaluation of different design and control strategies at a low cost. Machine Learning (ML) algorithms can leverage large-scale simulations to learn optimal
Externí odkaz:
http://arxiv.org/abs/2412.08293
Bell's states are among the most useful in quantum computing. These state are an orthonormal base of entagled states with two qubits. We propose alternative bases of entangled states. Some of these states depend on a continuous parameter. We present
Externí odkaz:
http://arxiv.org/abs/2409.06885
We show that quantum entanglement states are associated with multilinear polynomials that cannot be factored. By using these multilinear polynomials, we propose a geometric representation for entanglement states. In particular, we show that the Bell'
Externí odkaz:
http://arxiv.org/abs/2407.17621
Autor:
Manjavacas, Antonio, Campoy-Nieves, Alejandro, Jiménez-Raboso, Javier, Molina-Solana, Miguel, Gómez-Romero, Juan
Heating, Ventilation, and Air Conditioning (HVAC) systems are a major driver of energy consumption in commercial and residential buildings. Recent studies have shown that Deep Reinforcement Learning (DRL) algorithms can outperform traditional reactiv
Externí odkaz:
http://arxiv.org/abs/2401.05737
Post-stack seismic inversion is a widely used technique to retrieve high-resolution acoustic impedance models from migrated seismic data. Its modelling operator assumes that a migrated seismic data can be generated from the convolution of a source wa
Externí odkaz:
http://arxiv.org/abs/2401.00753
Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth. As such, it is widely utilized in the energy and construction sectors fo
Externí odkaz:
http://arxiv.org/abs/2312.10568
Autor:
Gijón, Alfonso, Pujana-Goitia, Ainhoa, Perea, Eugenio, Molina-Solana, Miguel, Gómez-Romero, Juan
The ever-growing use of wind energy makes necessary the optimization of turbine operations through pitch angle controllers and their maintenance with early fault detection. It is crucial to have accurate and robust models imitating the behavior of wi
Externí odkaz:
http://arxiv.org/abs/2307.14675
Publikováno v:
Volume 42 Issue 7 Jul 2023 Pages 446 516
4D seismic inversion is the leading method to quantitatively monitor fluid flow dynamics in the subsurface, with applications ranging from enhanced oil recovery to subsurface CO2 storage. The process of inverting seismic data for reservoir properties
Externí odkaz:
http://arxiv.org/abs/2303.11662
Autor:
Izzatullah, Muhammad, Alkhalifah, Tariq, Romero, Juan, Corrales, Miguel, Luiken, Nick, Ravasi, Matteo
Uncertainty quantification is crucial to inverse problems, as it could provide decision-makers with valuable information about the inversion results. For example, seismic inversion is a notoriously ill-posed inverse problem due to the band-limited an
Externí odkaz:
http://arxiv.org/abs/2212.14595
Even though a train/test split of the dataset randomly performed is a common practice, could not always be the best approach for estimating performance generalization under some scenarios. The fact is that the usual machine learning methodology can s
Externí odkaz:
http://arxiv.org/abs/2209.03346