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Showing posts with label Prediction. Show all posts
Showing posts with label Prediction. Show all posts
Thursday, 16 March 2023

Machine Learning to Predict the Adsorption Capacity of Microplastics

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 Nanomaterials 2023, 13(6), 1061 Nowadays, there is an extensive production and use of plastic materials for different industrial activities...
Wednesday, 14 December 2022

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

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 Mathematics 2022, 10(24), 4746 Global solar irradiation is an important variable that can be used to determine the suitability of an area t...
Wednesday, 21 April 2021

Modelling and Prediction of Monthly Global Irradiation Using Different Prediction Models

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 Energies 2021, 14(8), 2332 Different prediction models (multiple linear regression, vector support machines, artificial neural networks and...
Tuesday, 26 February 2019

Prediction Models to Control Aging Time in Red Wine

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Molecules 2019, 24(5), 826 DOI: 10.3390/molecules24050826 A combination of physical-chemical analysis has been used to monitor th...
Tuesday, 26 September 2017

Improved 1,3-propanediol production with maintained physical conditions and optimized media composition: Validation with statistical and neural approach

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Biochemical Engineering Journal https://doi.org/10.1016/j.bej.2017.07.003 This work is aimed at assessing the use of response sur...
Thursday, 15 June 2017

A critical review on the applications of artificial neural networks in winemaking technology

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Critical Reviews in Food Science and Nutrition http://dx.doi.org/10.1080/10408398.2015.1078277 Since their development in 1943, a...
Wednesday, 1 March 2017

Approach of Different Properties of Alkylammonium Surfactants using Artificial Intelligence and Response Surface Methodology

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Tenside, Surfactants and Detergents http://www.hanser-elibrary.com/doi/abs/10.3139/113.110483 Response surface methodology (RSM) ...
Thursday, 17 December 2015

Forecasting Olea Airborne Pollen Concentrations by Means of Artificial Intelligence

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Fresenius Environmental Bulletin, (2015) 24, 4574-4580 A model based in an Artificial Neural Network was de- veloped in order to fo...
Wednesday, 25 November 2015

Influence Prediction of Alkylamines Upon Electrical Percolation of AOT-based Microemulsions Using Artificial Neural Networks

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Tenside Surfactants Detergents, 52, 473-476 (2015) doi: 10.3139/113.110399 Simulations for the electrical percolation of AOT/iC8/...