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Cornejo Bueno, Laura María

Teoría de la Señal y Comunicaciones / Universidad de Alcalá

Actividades

Modelling the kinetics of stain removal from knitted cotton fabrics in a commercial Front Loader Washing Machine (FLWM)

  • Bueno, L.
  • Laso, C.
  • Amador, C.
  • Bakalis, S.

Chemical Engineering Science (p. 176-185) - 2019

Editor: Elsevier Ltd

10.1016/j.ces.2019.02.008 Ver en origen

  • ISSN/ISBN 0009-2509

Significant wave height and energy flux estimation with a Genetic Fuzzy System for regression

  • Cornejo-Bueno, L.
  • Rodríguez-Mier, P.
  • Mucientes, M.
  • Nieto-Borge, J.C.
  • Salcedo-Sanz, S.

Ocean Engineering (p. 33-44) - 2018

Editor: Elsevier Ltd

10.1016/j.oceaneng.2018.04.063 Ver en origen

  • ISSN/ISBN 0029-8018

Feature selection in machine learning prediction systems for renewable energy applications

  • Salcedo-Sanz, S.
  • Cornejo-Bueno, L.
  • Prieto, L.
  • Paredes, D.
  • García-Herrera, R.

Renewable and Sustainable Energy Reviews (p. 728-741) - 2018

Editor: Elsevier Ltd

10.1016/j.rser.2018.04.008 Ver en origen

  • ISSN/ISBN 1879-0690

Integrated biodiesel facilities: review of glycerol-based production of fuels and chemicals

  • Almena, A.
  • Bueno, L.
  • Díez, M.
  • Martín, M.

Clean Technologies and Environmental Policy (p. 1639-1661) - 2018

Editor: Springer Verlag

10.1007/s10098-017-1424-z Ver en origen

  • ISSN/ISBN 1618-9558

An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia

  • Salcedo-Sanz, S.
  • Deo, R.C.
  • Cornejo-Bueno, L.
  • Camacho-Gómez, C.
  • Ghimire, S.

Applied Energy (p. 79-94) - 2018

Editor: Elsevier Ltd

10.1016/j.apenergy.2017.10.076 Ver en origen

  • ISSN/ISBN 0306-2619

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

  • Yaseen, Z.M.
  • Deo, R.C.
  • Hilal, A.
  • Abd, A.M.
  • Bueno, L.C.
  • Salcedo-Sanz, S.
  • Nehdi, M.L.
... Ver más Contraer

Advances in Engineering Software (p. 112-125) - 2018

Editor: Elsevier Ltd

10.1016/j.advengsoft.2017.09.004 Ver en origen

  • ISSN/ISBN 1873-5339

Modeling the deposition of fluorescent whitening agents on cotton fabrics

  • Bueno, L.
  • Amador, C.
  • Bakalis, S.

AIChE Journal (p. 1305-1316) - 2018

Editor: John Wiley and Sons Inc.

10.1002/aic.16001 Ver en origen

  • ISSN/ISBN 1547-5905

Bayesian optimization of a hybrid system for robust ocean wave features prediction

  • Cornejo-Bueno, L.
  • Garrido-Merchán, E.C.
  • Hernández-Lobato, D.
  • Salcedo-Sanz, S.

NEUROCOMPUTING (p. 818-828) - 31/1/2018

Editor: Elsevier B.V.

10.1016/j.neucom.2017.09.025 Ver en origen

  • ISSN 09252312
  • ISSN/ISBN 1872-8286

Wind Power Ramp Events prediction with hybrid machine learning regression techniques and reanalysis data

  • Cornejo-Bueno, L.
  • Cuadra, L.
  • Jiménez-Fernández, S.
  • Acevedo-Rodríguez, J.
  • Prieto, L.
  • Salcedo-Sanz, S.

Energies - 2017

Editor: MDPI AG

10.3390/en10111784 Ver en origen

  • ISSN/ISBN 1996-1073

Efficient Prediction of Low-Visibility Events at Airports Using Machine-Learning Regression

  • Cornejo-Bueno, L.
  • Casanova-Mateo, C.
  • Sanz-Justo, J.
  • Cerro-Prada, E.
  • Salcedo-Sanz, S.

Boundary-Layer Meteorology (p. 349-370) - 2017

Editor: Springer Netherlands

10.1007/s10546-017-0276-8 Ver en origen

  • ISSN/ISBN 1573-1472

Este/a investigador/a no tiene libros.

Introduction to gPROMS® for chemical engineering

  • Amador, C.
  • Martín, M.
  • Bueno, L.

Introduction to Software for Chemical Engineers, Second Editionw (p. 373-459) - 2019

Editor: CRC Press

10.1201/9780429451010-10 Ver en origen

  • ISSN/ISBN 9781138324220

A hybrid ensemble of heterogeneous regressors for wind speed estimation in wind farms

  • Cornejo-Bueno, L.
  • Acevedo-Rodríguez, J.
  • Prieto, L.
  • Salcedo-Sanz, S.

Studies in Computational Intelligence (p. 97-106) - 2018

Editor: Springer Verlag

10.1007/978-3-319-99626-4_9 Ver en origen

  • ISSN/ISBN 1860-949X

Scale-up and Techno-economical Study for the Production of Polyesters from Glycerol

  • Bueno, L.
  • Toro, C.A.
  • Martín, M.

Computer Aided Chemical Engineering (p. 43-48) - 2014

Editor: Elsevier B.V.

10.1016/b978-0-444-63456-6.50008-9 Ver en origen

  • ISSN/ISBN 1570-7946

Downscaling estadístico del servicio CAMS para la predicción de radiación solar global con datos Meteosat y técnicas de aprendizaje máquina

  • Laura María Cornejo Bueno
  • Carlos Casanova Mateo
  • María Julia Sanz Justo
  • Diego Gómez Aragón
  • P. Salvador
  • Sancho Salcedo Sanz
  • José Luis Casanova Roque
... Ver más Contraer

Teledetección: hacia una visión global del cambio climático (p. 229-232) - 2019

Editor: Ediciones Universidad de Valladolid (EdUVa)

  • ISSN/ISBN 978-84-1320-038-5

Merging ELMs with satellite data and clear-sky models for effective solar radiation estimation

  • Cornejo-Bueno, L.
  • Casanova-Mateo, C.
  • Sanz-Justo, J.
  • Salcedo-Sanz, S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (p. 163-170) - 2018

Editor: Springer Verlag

10.1007/978-3-030-03496-2_19 Ver en origen

  • ISSN/ISBN 1611-3349

A grouping genetic algorithm - Extreme learning machine approach for optimal wave energy prediction

  • Cornejo-Bueno, L.
  • Aybar-Ruiz, A.
  • Jimenez-Fernandez, S.
  • Alexandre, E.
  • Nieto-Borge, J.C.
  • Salcedo-Sanz, S.

2016 IEEE Congress on Evolutionary Computation, CEC 2016 (p. 3817-3823) - 2016

Editor: Institute of Electrical and Electronics Engineers Inc.

10.1109/cec.2016.7744273 Ver en origen

  • ISSN/ISBN 9781509006229

Optimal placement of distributed generation in micro-grids with binary and integer-encoding evolutionary algorithms

  • Camacho-Gomez, C.
  • Mallol-Poyato, R.
  • Jimenez-Fernandez, S.
  • Cornejo-Bueno, L.
  • Salcedo-Sanz, S.

2016 IEEE Congress on Evolutionary Computation, CEC 2016 (p. 3630-3637) - 2016

Editor: Institute of Electrical and Electronics Engineers Inc.

10.1109/cec.2016.7744249 Ver en origen

  • ISSN/ISBN 9781509006229

Feature selection with a grouping genetic algorithm – Extreme learning machine approach for wind power prediction

  • Cornejo-Bueno, L.
  • Camacho-Gómez, C.
  • Aybar-Ruiz, A.
  • Prieto, L.
  • Salcedo-Sanz, S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (p. 373-382) - 2016

Editor: Springer Verlag

10.1007/978-3-319-44636-3_35 Ver en origen

  • ISSN/ISBN 1611-3349

Modelling the deposition of Fluorescent Whitening Agents (FWAs) on flat woven cotton fabrics

  • Bueno, L.
  • Amador, C.
  • Bakalis, S.

22nd International Congress of Chemical and Process Engineering, CHISA 2016 and 19th Conference on Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction, PRES 2016 (p. 10-11) - 2016

Editor: Czech Society of Chemical Engineering

  • ISSN/ISBN 9781510859623

Modelling the deposition of actives on cotton fabrics during the washing process

  • Bueno, L.
  • Amador, C.
  • Bakalis, S.

Process Development Division 2016 - Core Programming Area at the 2016 AIChE Meeting (p. 129-131) - 2016

Editor: AIChE

  • ISSN/ISBN 9781510834460

Nested evolutionary algorithms for joint structure design and operation of micro-grids under variable electricity prices scenarios

  • Mallol-Poyato, R.
  • Jimenez-Fernandez, S.
  • Cornejo-Bueno, L.
  • Diaz-Villar, P.
  • Salcedo-Sanz, S.

INISTA 2015 - 2015 International Symposium on Innovations in Intelligent SysTems and Applications, Proceedings - 2015

Editor: Institute of Electrical and Electronics Engineers Inc.

10.1109/inista.2015.7276735 Ver en origen

  • ISSN/ISBN 9781467390965

Energy flux range classification by using a dynamic window autoregressive model

  • Gutiérrez, P.A.
  • Fernández, J.C.
  • Pérez-Ortiz, M.
  • Cornejo-Bueno, L.
  • Alexandre-Cortizo, E.
  • Salcedo-Sanz, S.
  • Hervás-Martínez, C.
... Ver más Contraer

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (p. 92-102) - 2015

Editor: Springer Verlag

10.1007/978-3-319-19222-2_8 Ver en origen

  • ISSN/ISBN 1611-3349

Este/a investigador/a no tiene documentos de trabajo.

Este/a investigador/a no tiene informes técnicos.

Este/a investigador/a no tiene proyectos de investigación.

Este/a investigador/a no tiene tesis dirigidas.

Este/a investigador/a no tiene patentes o licencias de software.

Última actualización de los datos: 24/04/24 13:21