Publicacións nas que colabora con PAULINO JOSE GARCIA NIETO (83)

2024

  1. Numerical model for determining the effective heat capacity of macroencapsulated PCM for building applications

    Applied Thermal Engineering, Vol. 242

  2. 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

  1. A support vector regression model for time series forecasting of the COMEX copper spot price

    Logic Journal of the IGPL, Vol. 31, Núm. 4, pp. 775-784

  2. Method for the Detection of Functional Outliers Applied to Quality Monitoring Samples in the Vicinity of El Musel Seaport in the Metropolitan Area of Gijón (Northern Spain)

    Mathematics, Vol. 11, Núm. 12

2021

  1. A Multivariate Approach to Time Series Forecasting of Copper Prices with the Help of Multiple Imputation by Chained Equations and Multivariate Adaptive Regression Splines

    Advances in Intelligent Systems and Computing

  2. 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

  3. 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

  4. Time Series Analysis for the COMEX Copper Spot Price by Using Support Vector Regression

    Advances in Intelligent Systems and Computing

2020

  1. 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

  2. Chrome Layer Thickness Modelling in a Hard Chromium Plating Process Using a Hybrid PSO/ RBF–SVM–Based Model

    IJIMAI, Vol. 6, Núm. 4, pp. 39-48

  3. Predicting benzene concentration using machine learning and time series algorithms

    Mathematics, Vol. 8, Núm. 12, pp. 1-21

2019

  1. 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

  1. 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

  2. Numerical investigation of truck aerodynamics on several classes of infrastructures

    Wind and Structures, An International Journal, Vol. 26, Núm. 1, pp. 35-43

  3. Optimización de estructuras de acero con un algoritmo genético y tres códigos de construcción internacionales

    Revista de la Construcción, Vol. 17, Núm. 1, pp. 47-59

2016

  1. 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

  2. Hard-rock stability analysis for span design in entry-type excavations with learning classifiers

    Materials, Vol. 9, Núm. 7

  3. Hybrid ABC optimized MARS-based modeling of the milling tool wear from milling run experimental data

    Materials, Vol. 9, Núm. 2

2014

  1. Hygrothermal study of lightweight concrete hollow bricks: A new proposed experimental-numerical method

    Energy and Buildings, Vol. 70, pp. 194-206

  2. The use of response surface methodology to improve the thermal transmittance of lightweight concrete hollow bricks by FEM

    Construction and Building Materials, Vol. 52, pp. 331-344