Výsledky vyhledávání - "Latifa Khaouane"

Akademický článek

A Comparison of 'Neural Networks and Multiple Linear Regressions' Models to Describe the Rejection of Micropollutants by Membranes

Autor: Yamina Ammi, Latifa Khaouane, Salah Hanini

Publikováno v: Kemija u Industriji, Vol 69, Iss 3-4, Pp 111-127 (2020)

A rejection process of organic compounds by nanofiltration and reverse osmosis membranes was modelled using the artificial neural networks. Three feed-forward neural networks based on quantitative structure-activity relationship (QSAR-NN models) char

Externí odkaz: https://doaj.org/article/58b1dc70529844438e17031a210722f0

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Akademický článek

QSPR Studies of Carbonyl, Hydroxyl, Polyene Indices, and Viscosity Average Molecular Weight of Polymers under Photostabilization Using ANN and MLR Approaches

Autor: Hadjira Maouz, Latifa Khaouane, Salah Hanini, Yamina Ammi, Mabrouk Hamadache, Maamar Laidi

Publikováno v: Kemija u Industriji, Vol 69, Iss 1-2, Pp 1-16 (2020)

One of the main disadvantages of the use of synthetic or semi-synthetic polymeric materials is their degradation and aging. The purpose of this study was to use artificial neural networks (ANN) and multiple linear regressions (MLR) to predict the car

Externí odkaz: https://doaj.org/article/387ebc5158b44f3290acd485df96fbb8

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Akademický článek

Comparative Study of Predicting the Molecular Diffusion Coefficient for Polar and Non-polar Binary Gas Using Neural Networks and Multiple Linear Regressions

Autor: Naima Melzi, Latifa Khaouane, Yamina Ammi, Salah Hanini, Maamar Laidi, Hamid Zentou

Publikováno v: Kemija u Industriji, Vol 68, Iss 11-12, Pp 573-582 (2019)

In the current study, an artificial neural network (ANN) and multiple linear regressions (MLR) have been used to develop predictive models for the estimation of molecular diffusion coefficients of 1252 polar and non-polar binary gases at multiple pre

Externí odkaz: https://doaj.org/article/53b7df66a92e42f8ae1319a6cbaf414b

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Akademický článek

Modelling of Adsorption of Methane, Nitrogen, Carbon Dioxide, Their Binary Mixtures, and Their Ternary Mixture on Activated Carbons Using Artificial Neural Network

Autor: Hadjer Barki, Latifa Khaouane, Salah Hanini

Publikováno v: Kemija u Industriji, Vol 68, Iss 7-8, Pp 289-302 (2019)

This work examines the use of neural networks in modelling the adsorption process of gas mixtures (CO2, CH4, and N2) on different activated carbons. Seven feed-forward neural network models, characterized by different structures, were constructed wit

Externí odkaz: https://doaj.org/article/f5db50b3e00d421082720f5b2d3ff2fc

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Akademický článek

Prediction of Climatic Parameters from Physicochemical Parameters using Artificial Neural Networks: Case Study of Ain Defla (Algeria)

Autor: Lamia Gheraba, Latifa Khaouane, Othmane Benkortbi, Salah Hanini, Mabrouk Hamadache

Publikováno v: Kemija u Industriji, Vol 68, Iss 7-8, Pp 303-316 (2019)

The knowledge of the climate of a region is a primordial task in that it allows predictions of climatic parameters in the future. In this study, monthly maximum and minimum air temperature (Tair,min, Tair,max), relative humidity (RH), and sunshine du

Externí odkaz: https://doaj.org/article/6c40f1987b4847aba37923b15d4a6a4b

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Akademický článek

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Development of QSPR-ANN models for the estimation of critical properties of pure hydrocarbons

Autor: Mohamed Roubehie Fissa, Yasmina Lahiouel, Latifa Khaouane, Salah Hanini

Publikováno v: Journal of Molecular Graphics and Modelling. 121:108450

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::879726e2cfdea5a4feeb14eb36efd392
https://doi.org/10.1016/j.jmgm.2023.108450

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An artificial intelligence approach for modeling the rejection of anti-inflammatory drugs by nanofiltration and reverse osmosis membranes using kernel support vector machine and neural networks

Autor: Salah Hanini, Yamina Ammi, Latifa Khaouane

Publikováno v: Comptes Rendus. Chimie. 24:243-254

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f723da3a35139a6c9788d1c3d6acd512
https://doi.org/10.5802/crchim.76

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Stacked neural networks for predicting the membranes performance by treating the pharmaceutical active compounds

Autor: Yamina Ammi, Latifa Khaouane, Salah Hanini

Publikováno v: Neural Computing and Applications. 33:12429-12444

The removal of pharmaceutical actives compounds (PhACs) by nanofiltration (NF) and reverse osmosis (RO) of paramount importance in membrane separation processes. However, modeling remains a difficult approach due to the strongly nonlinear performance

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::76ca1164382b1f7385fd04a3b2c4d01b
https://doi.org/10.1007/s00521-021-05876-0

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Optimization Methodology of Artificial Neural Network Models for Predicting Molecular Diffusion Coefficients for Polar and Non-Polar Binary Gases

Autor: Maamar Laidi, Hamid Zentou, Naima Melzi, Latifa Khaouane, Salah Hanini, Yamina Ammi

Publikováno v: Journal of Applied Mechanics and Technical Physics. 61:207-216

In this study, an artificial neural network (ANN) is used to develop predictive models for estimating molecular diffusion coefficients of various gases at multiple pressures over a large field of temperatures. Two feed-forward neural networks NN1 and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8d66f97c92f9ac931de4f7c7e320313e
https://doi.org/10.1134/s0021894420020066

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