Publicacións nas que colabora con JUAN CARLOS MEJUTO FERNANDEZ (16)

2024

  1. Ionic surfactants critical micelle concentration prediction in water/organic solvent mixtures by artificial neural network

    Tenside, Surfactants, Detergents

2023

  1. Machine Learning to Predict the Adsorption Capacity of Microplastics

    Nanomaterials, Vol. 13, Núm. 6

2022

  1. Global Solar Irradiation Modelling and Prediction Using Machine Learning Models for Their Potential Use in Renewable Energy Applications

    Mathematics, Vol. 10, Núm. 24

2021

  1. Machine learning applied to the oxygen-18 isotopic composition, salinity and temperature/potential temperature in the mediterranean sea

    Mathematics, Vol. 9, Núm. 19

2018

  1. Aldehydes as additives in AOT-based microemulsions: Influence on the electrical percolation

    Tenside, Surfactants, Detergents, Vol. 55, Núm. 2, pp. 110-115

  2. Future challenges on the use of blockchain for food traceability analysis

    TrAC - Trends in Analytical Chemistry, Vol. 107, pp. 222-232

2015

  1. Forecasting Olea airborne pollen concentration by means of artificial intelligence

    Fresenius Environmental Bulletin, Vol. 24, Núm. 12B, pp. 4574-4580

  2. Influence prediction of alkylamines upon electrical percolation of AOT-based microemulsions using artificial neural networks

    Tenside, Surfactants, Detergents, Vol. 52, Núm. 6, pp. 473-476

2013

  1. Esters flash point prediction using artificial neural networks

    Journal of Computational Chemistry, Vol. 34, Núm. 5, pp. 355-359

2011

  1. Erratum: Prediction of prop-2-enoate polymer and styrene polymer glass transition using artificial neural networks (Journal of Chemical & Engineering Data (2010) 55 (5340-5346))

    Journal of Chemical and Engineering Data

  2. Erratum: Prediction of refractive index of polymers using artificial neural networks (Journal of Chemical & Engineering Data (2010) 55 (5388-5393))

    Journal of Chemical and Engineering Data

2010

  1. Artificial neural networks: a promising tool to evaluate the authenticity of wine

    CyTA: Journal of food, Vol. 8, Núm. 1, pp. 73-78

  2. Prediction of Prop-2-enoate polymer and styrene polymer glass transition using artificial neural networks

    Journal of Chemical and Engineering Data, Vol. 55, Núm. 11, pp. 5340-5346

  3. Prediction of ethene + oct-1-ene copolymerization ideal conditions using artificial neuron networks

    Journal of Chemical and Engineering Data, Vol. 55, Núm. 9, pp. 3542-3547

  4. Prediction of refractive index of polymers using artificial neural networks

    Journal of Chemical and Engineering Data, Vol. 55, Núm. 11, pp. 5388-5393

2009

  1. Redes Neuronales Artificiales, una herramienta prometedora para evaluar la autenticidad de los vinos: Relación entre las propiedades fisicoquímicas y el proceso de vinificación

    Nuevos horizontes en la viticultura y enología: X Congreso Nacional de Investigación Enológica. Ourense, del 3 al 5 de junio de 2009