Search Results - "SANZ, S"

Direct Capture of CO2 from Ambient Air by Sanz-Pérez, Eloy S, Murdock, Christopher R, Didas, Stephanie A, Jones, Christopher W

“…The increase in the global atmospheric CO2 concentration resulting from over a century of combustion of fossil fuels has been associated with significant…”
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Heat Waves: Physical Understanding and Scientific Challenges by Barriopedro, D., García‐Herrera, R., Ordóñez, C., Miralles, D. G., Salcedo‐Sanz, S.

“…Heat waves (HWs) can cause large socioeconomic and environmental impacts. The observed increases in their frequency, intensity and duration are projected to…”
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Young's Experiment with Entangled Bipartite Systems: The Role of Underlying Quantum Velocity Fields by Sanz, Angel S

“…We consider the concept of velocity fields, taken from Bohmian mechanics, to investigate the dynamical effects of entanglement in bipartite realizations of…”
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Machine learning regressors for solar radiation estimation from satellite data by Cornejo-Bueno, L., Casanova-Mateo, C., Sanz-Justo, J., Salcedo-Sanz, S.

“…•A problem of global solar regression from satellite data and physical models is tackled.•Machine Learning regression techniques are applied.•Comparison of…”
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Exploring the dynamics of finite-energy Airy beams: a trajectory analysis perspective by Sanz, Ángel S, Martínez-Herrero, Rosario

“…In practice, Airy beams can only be reproduced in an approximate manner, with a limited spatial extension and hence a finite energy content. To this end,…”
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Feature selection in machine learning prediction systems for renewable energy applications by Salcedo-Sanz, S., Cornejo-Bueno, L., Prieto, L., Paredes, D., García-Herrera, R.

“…This paper focuses on feature selection problems that arise in renewable energy applications. Feature selection is an important problem in machine learning,…”
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A review on the coral reefs optimization algorithm: new development lines and current applications by Salcedo-Sanz, S.

“…The simulation of biological processes has produced some of the most important meta-heuristics algorithms for optimization. Evolutionary algorithms were the…”
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Multi-fractal multi-resolution structures from DLA – Strange Attractors Hybrids by Salcedo-Sanz, S., Cuadra, L.

“…•We describe and simulate multi-fractal multi-resolution structures.•Hybrid Diffusion Limited Aggregation - Strange Attractors are proposed.•Super-Cumulus of…”
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Quantum-Classical Entropy Analysis for Nonlinearly-Coupled Continuous-Variable Bipartite Systems by Sanz, Ángel S

“…The correspondence principle plays a fundamental role in quantum mechanics, which naturally leads us to inquire whether it is possible to find or determine…”
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Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach by Salcedo-Sanz, S., Pastor-Sánchez, A., Prieto, L., Blanco-Aguilera, A., García-Herrera, R.

“…•A novel approach for short-term wind speed prediction is presented.•The system is formed by a coral reefs optimization algorithm and an extreme learning…”
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Applied Bohmian mechanics by Benseny, Albert, Albareda, Guillermo, Sanz, Ángel S., Mompart, Jordi, Oriols, Xavier

“…Bohmian mechanics provides an explanation of quantum phenomena in terms of point-like particles guided by wave functions. This review focuses on the use of…”
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Daily global solar radiation prediction based on a hybrid Coral Reefs Optimization – Extreme Learning Machine approach by Salcedo-Sanz, S., Casanova-Mateo, C., Pastor-Sánchez, A., Sánchez-Girón, M.

“…•This paper presents a hybrid CRO–ELM algorithm for solar radiation prediction.•Novel predictive meteorological variables are considered in this problem.•The…”
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Analysis of the gradual transition from the near to the far field in single-slit diffraction by García-Sánchez, Almudena, Sanz, Ángel S

“…In Optics it is common to split up the formal analysis of diffraction according to two convenient approximations, in the near and far fields (also known as the…”
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Experimental verification of the boundary conditions in the success of the Brazilian test with loading arcs. An uncertainty approach using concrete disks by Gutiérrez-Moizant, R., Ramírez-Berasategui, M., Sánchez-Sanz, S., Santos-Cuadros, S.

“…The present work analyses the reliability of the Brazilian test with loading arcs. A new testing set up has allowed to determine in an effective way the real…”
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Computational intelligence in wave energy: Comprehensive review and case study by Cuadra, L., Salcedo-Sanz, S., Nieto-Borge, J.C., Alexandre, E., Rodríguez, G.

“…Wind-generated wave energy is a renewable energy source that exhibits a huge potential for sustainable growth. The design and deployment of wave energy…”
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The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems by Gil-López, S., Landa-Torres, I., Del Ser, J., Salcedo-Sanz, S., Portilla-Figueras, J. A.

“…This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm…”
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Evolutionary artificial neural networks for accurate solar radiation prediction by Guijo-Rubio, D., Durán-Rosal, A.M., Gutiérrez, P.A., Gómez-Orellana, A.M., Casanova-Mateo, C., Sanz-Justo, J., Salcedo-Sanz, S., Hervás-Martínez, C.

“…This paper evaluates the performance of different evolutionary neural network models in a problem of solar radiation prediction at Toledo, Spain. The…”
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A survey on applications of the harmony search algorithm by Manjarres, D., Landa-Torres, I., Gil-Lopez, S., Del Ser, J., Bilbao, M.N., Salcedo-Sanz, S., Geem, Z.W.

“…This paper thoroughly reviews and analyzes the main characteristics and application portfolio of the so-called Harmony Search algorithm, a meta-heuristic…”
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Structures vibration control via Tuned Mass Dampers using a co-evolution Coral Reefs Optimization algorithm by Salcedo-Sanz, S., Camacho-Gómez, C., Magdaleno, A., Pereira, E., Lorenzana, A.

“…In this paper we tackle a problem of optimal design and location of Tuned Mass Dampers (TMDs) for structures subjected to earthquake ground motions, using a…”
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Multi-task learning for the prediction of wind power ramp events with deep neural networks by Dorado-Moreno, M., Navarin, N., Gutiérrez, P.A., Prieto, L., Sperduti, A., Salcedo-Sanz, S., Hervás-Martínez, C.

“…In Machine Learning, the most common way to address a given problem is to optimize an error measure by training a single model to solve the desired task…”
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