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Esperanza García–Gonzalo

Observed names: E. García Gonzalo, E. García-Gonzalo, E. García–Gonzalo, ESPERANZA GARCÍA-GONZALO, Esperanza Garcia Gonzalo, Esperanza Garcia-Gonzalo, Esperanza García Gonzalo, Esperanza García- Gonzalo, Esperanza García-Gonzalo, García Gonzalo, María Esperanza, García-Gonzalo, E., M. E. García-Gonzalo
Observed institutions: Mayo Clinic, University of Lisbon, Universidad de Oviedo, Weill Cornell Medical College in Qatar, Bureau de Recherches Géologiques et Minières, Université Bordeaux-I, Universidade de Vigo, University of California, Berkeley, Stanford University
ORCID: 0000-0002-3194-4448
Observed ORCID: 0000-0002-3194-4448
OpenAlex ID: A5036495170
Hybrid PSO–SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability
2015 · P.J. García Nieto, E. García-Gonzalo, et al. · Reliability Engineering & System Safety · 321
PM10 concentration forecasting in the metropolitan area of Oviedo (Northern Spain) using models based on SVM, MLP, VARMA and ARIMA: A case study
2017 · P.J. García Nieto, F. Sánchez Lasheras, et al. · The Science of The Total Environment · 195
PSO: A powerful algorithm to solve geophysical inverse problems
2010 · Juan L. Fernández Martínez, Esperanza García Gonzalo, et al. · Journal of Applied Geophysics · 182
A Brief Historical Review of Particle Swarm Optimization (PSO)
2012 · E. García-Gonzalo, J. L. Fernández-Martínez · Journal of Bioinformatics and Intelligent Control · 173
Stochastic Stability Analysis of the Linear Continuous and Discrete PSO Models
2010 · Juan Luis Fernandez-Martinez, Esperanza Garcia-Gonzalo · IEEE Transactions on Evolutionary Computation · 166
The Generalized PSO: A New Door to PSOEvolution
2008 · J. L. Fernández Martínez, E. García Gonzalo · Journal of Artificial Evolution and Applications · 108
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The PSO family: deduction, stochastic analysis and comparison
2009 · J. L. Fernández Martínez, E. García Gonzalo · Swarm Intelligence · 104
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Forecast of the higher heating value in biomass torrefaction by means of machine learning techniques
2019 · P.J. García Nieto, E. García–Gonzalo, et al. · Journal of Computational and Applied Mathematics · 83
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Particle swarm optimization applied to solving and appraising the streaming-potential inverse problem
2010 · Juan Luis Fernández-Martínez, Esperanza García-Gonzalo, et al. · Geophysics · 73
A comparison of several machine learning techniques for the centerline segregation prediction in continuous cast steel slabs and evaluation of its performance
2017 · P.J. García Nieto, E. García-Gonzalo, et al. · Journal of Computational and Applied Mathematics · 72
Hard-Rock Stability Analysis for Span Design in Entry-Type Excavations with Learning Classifiers
2016 · Esperanza García-Gonzalo, Zulima Fernández-Muñiz, et al. · Materials · 68
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Prediction of the critical temperature of a superconductor by using the WOA/MARS, Ridge, Lasso and Elastic-net machine learning techniques
2021 · Paulino José García-Nieto, Esperanza García-Gonzalo, et al. · Neural Computing and Applications · 66
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Theoretical analysis of particle swarm trajectories through a mechanical analogy
2008 · J.L. Fernández-Martínez, E. García-Gonzalo, et al. · International Journal of Computational Intelligence Research · 62
A hybrid PSO optimized SVM-based model for predicting a successful growth cycle of the Spirulina platensis from raceway experiments data
2015 · P.J. García Nieto, E. García-Gonzalo, et al. · Journal of Computational and Applied Mathematics · 60
Predictive modelling of the higher heating value in biomass torrefaction for the energy treatment process using machine-learning techniques
2018 · P. J. García Nieto, E. García-Gonzalo, et al. · Neural Computing and Applications · 58
Water eutrophication assessment relied on various machine learning techniques: A case study in the Englishmen Lake (Northern Spain)
2019 · P.J. García Nieto, E. García-Gonzalo, et al. · Ecological Modelling · 55
Reservoir characterization and inversion uncertainty via a family of particle swarm optimizers
2012 · Juan Luis Fernández Martínez, Tapan Mukerji, et al. · Geophysics · 55
Hybrid PSO–SVM-based method for long-term forecasting of turbidity in the Nalón river basin: A case study in Northern Spain
2014 · P.J. García Nieto, E. García-Gonzalo, et al. · Ecological Engineering · 52
A new predictive model based on the PSO-optimized support vector machine approach for predicting the milling tool wear from milling runs experimental data
2015 · P. J. García-Nieto, E. García-Gonzalo, et al. · The International Journal of Advanced Manufacturing Technology · 47
Convergence and stochastic stability analysis of particle swarm optimization variants with generic parameter distributions
2014 · Esperanza García-Gonzalo, Juan Luis Fernández-Martínez · Applied Mathematics and Computation · 41
Modelling hydrogen production from biomass pyrolysis for energy systems using machine learning techniques
2023 · Paulino José García-Nieto, Esperanza García-Gonzalo, et al. · Environmental Science and Pollution Research · 39
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Particle Swarm Optimization (PSO): a simple and powerful algorithm family for geophysical inversion
2008 · J. L. Fernandez-Martinez, J. P. Fernández-Alvarez, et al. · Second International Meeting for Applied Geoscience & Energy · 38
A New Predictive Model for the State-of-Charge of a High-Power Lithium-Ion Cell Based on a PSO-Optimized Multivariate Adaptive Regression Spline Approach
2015 · Juan Carlos Alvarez Anton, Paulino J. Garcia Nieto, et al. · IEEE Transactions on Vehicular Technology · 33
A hybrid PSO optimized SVM-based method for predicting of the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir: A case study in Northern Spain
2015 · P.J. García Nieto, J.R. Alonso Fernández, et al. · Applied Mathematics and Computation · 33
Forecast of chlorophyll-a concentration as an indicator of phytoplankton biomass in El Val reservoir by utilizing various machine learning techniques: A case study in Ebro river basin, Spain
2024 · Paulino José García–Nieto, Esperanza García–Gonzalo, et al. · Journal of Hydrology · 29
Works count: 114
Citation count: 3,046
H-index: 28
I10-index: 61
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