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Showing posts with label Artificial Neural Networks. Show all posts
Showing posts with label Artificial Neural Networks. Show all posts
Saturday, 1 February 2020

Random Forest, Artificial Neural Network, and Support Vector Machine Models for Honey Classification

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eFood, 2020, 1(1) 69-76 Different separated protein fractions by the electrophoretic method in polyacrylamide gel were used to classify two ...
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...
Saturday, 14 July 2018

Modelling and Optimization of Biogenic Synthesis of Gold Nanoparticles from Leaf Extract of Swertia chirata Using Artificial Neural Network

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 J Clust Sci 29, 1151–1159 (2018) Swertia chirata is a medicinal plant studied for its ability to synthesize polyshaped gold nanoparticles (...

Modelling and Optimization of Biogenic Synthesis of Gold Nanoparticles from Leaf Extract of Swertia chirata Using Artificial Neural Network

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Journal of Cluster Science (2018) 29:1151–1159 DOI: 10.1007/s10876-018-1429-8 Swertia chirata is a medicinal plant studied for i...
Thursday, 1 February 2018

A critical review on the use of artificial neural networks in olive oil production, characterization and authentication

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Critical Reviews in Food Science and Nutrition  doi.org/10.1080/10408398.2018.1433628 Artificial neural networks (ANN) are computa...
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) ...
Monday, 12 December 2016

Approach of different properties of alkylammonium surfactants using artificial intelligence and response surface methodology

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Tenside, Surfactants, Detergents Response surface methodology (RSM) and artificial neural networks (ANNs) architectures to predict ...
Tuesday, 12 January 2016

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain

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Water Science & Technology (2016) DOI: 10.2166/wst.2016.002 Transit data analysis and artificial neural networks (ANNs) have ...
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...
Monday, 7 December 2015

Electrical Percolation of AOT-based Microemulsions with n-Alcohols

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Journal of Molecular Liquids DOI: 10.1016/j.molliq.2015.12.021 Percolative behaviour of w/o AOT/iC8/H2O microemulsions added with...
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/...
Wednesday, 21 October 2015

A Critical Review on the Applications of Artificial Neural Networks in Winemaking Technology

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Critical Reviews in Food Science and Nutrition DOI:10.1080/10408398.2015.1078277 Since their development in 1943, artificial neur...
Thursday, 15 October 2015

Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs)

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PLOS ONE DOI: 10.1371/journal.pone.0128566 There are a large number of tomato cultivars with a wide range of morphological, chemi...
Thursday, 1 October 2015

Linear Polyethers as Additives for AOT-Based Microemulsions: Prediction of Percolation Temperature Changes Using Artificial Neural Networks

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Tenside Surfactants Detergents: 52 (2015) 264-270. doi: 10.3139/113.110374   Predictive models based on artificial neural netwo...
Tuesday, 2 June 2015

A model to forecast the risk periods of Plantago pollen allergy by using the ANN methodology

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Aerobiologia (2015) 31:201–211 DOI 10.1007/s10453-014-9357-z Some biological particles present in the atmosphere, such as pollen ...
Tuesday, 24 February 2015

A model to forecast the risk periods of Plantago pollen allergy by using the ANN methodology

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Aerobiología (2015) DOI: 10.1007/s10453-014-9357-z Some biological particles present in the atmosphere, such as pollen grains, gi...