PAULINO JOSE
GARCIA NIETO
Catedrático de Universidad
Universidad de León
León, EspañaPublicacions en col·laboració amb investigadors/es de Universidad de León (13)
2024
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Predicting the critical superconducting temperature using the random forest, MLP neural network, M5 model tree and multivariate linear regression
Alexandria Engineering Journal, Vol. 86, pp. 144-156
2023
2021
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A new hybrid model to foretell thermal power efficiency from energy performance certificates at residential dwellings applying a Gaussian process regression
Neural Computing and Applications, Vol. 33, Núm. 12, pp. 6627-6640
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Modelling energy performance using a new hybrid DE/MARS–based approach for fossil-fuel thermal power stations
Environmental Science and Pollution Research, Vol. 28, Núm. 4, pp. 4417-4429
2020
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A hybrid predictive approach for chromium layer thickness in the hard chromium plating process based on the differential evolution/gradient boosted regression tree methodology
Mathematics, Vol. 8, Núm. 6
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A methodology for detecting relevant single nucleotide polymorphism in prostate cancer with multivariate adaptive regression splines and backpropagation artificial neural networks
Neural Computing and Applications, Vol. 32, Núm. 5, pp. 1231-1238
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Predicting benzene concentration using machine learning and time series algorithms
Mathematics, Vol. 8, Núm. 12, pp. 1-21
2019
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Predictive modelling of the higher heating value in biomass torrefaction for the energy treatment process using machine-learning techniques
Neural Computing and Applications, Vol. 31, Núm. 12, pp. 8823-8836
2018
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Air Quality Modeling Using the PSO-SVM-Based Approach, MLP Neural Network, and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)
Environmental Modeling and Assessment, Vol. 23, Núm. 3, pp. 229-247
2016
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A new predictive model based on the abc optimized multivariate adaptive regression splines approach for predicting the remaining useful life in aircraft engines
Energies, Vol. 9, Núm. 6
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Hard-rock stability analysis for span design in entry-type excavations with learning classifiers
Materials, Vol. 9, Núm. 7
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Hybrid ABC optimized MARS-based modeling of the milling tool wear from milling run experimental data
Materials, Vol. 9, Núm. 2
2011
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Analysis of the influence of forest environments on the accuracy of GPS measurements by using genetic algorithms
Mathematical and Computer Modelling, Vol. 54, Núm. 7-8, pp. 1829-1834