[HTML][HTML] A comparison of artificial intelligence models for predicting phosphate removal efficiency from wastewater using the electrocoagulation process

MG Shirkoohi, RD Tyagi, PA Vanrolleghem… - Digital Chemical …, 2022 - Elsevier
In this study, artificial intelligence (AI) models including adaptive neuro-fuzzy inference
systems (ANFIS), artificial neural networks (ANN), and support vector regression (SVR) were …

Data-based flow rate prediction models for independent metering hydraulic valve

W Su, W Ren, H Sun, C Liu, X Lu, Y Hua, H Wei, H Jia - Energies, 2022 - mdpi.com
Accurate valve flow rate prediction is essential for the flow control process of independent
metering (IM) hydraulic valve. Traditional estimation methods are difficult to meet the high …

Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three‐Phase Power Transformer Winding Conductors

F Valencia, H Arcos, F Quilumba - Journal of Electrical and …, 2021 - Wiley Online Library
This research compares four machine learning techniques: linear regression, support vector
regression, random forests, and artificial neural networks, with regard to the determination of …

Determinación de la vida residual de los devanados de transformadores de potencia mediante el análisis de la fatiga acumulada causada por fuerzas …

FR Valencia Arcos - 2024 - bibdigital.epn.edu.ec
In this research, a method is proposed to analyze the consequences of mechanical fatigue
on the useful life of power transformers, considering all operating conditions. The typical …

Mechanical Stress in Power Transformer Winding Conductors: A Support Vector Regression Approach

F Valencia, H Arcos, F Quilumba - … and Electronics: Proceedings of the JIEE …, 2022 - Springer
A support vector regression model to determine the mechanical stress in winding conductors
of a power transformer was developed in this research. Only the hyperparameter C, related …

[PDF][PDF] Digital Chemical Engineering

MG Shirkoohi, RD Tyagi, PA Vanrolleghem, P Drogui - researchgate.net
abstract In this study, artificial intelligence (AI) models including adaptive neuro-fuzzy
inference systems (ANFIS), artificial neural networks (ANN), and support vector regression …

Techniques d'intelligence artificielle dans la modélisation du processus électrochimique pour le traitement des eaux résiduaires.

M Gholami Shirkoohi - 2022 - espace.inrs.ca
La transcription des symboles et des caractères spéciaux utilisés dans la version originale
de ce résumé n'a pas été possible en raison de limitations techniques. La version correcte …

[PDF][PDF] Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve. Energies 2022, 15, 7699

W Su, W Ren, H Sun, C Liu, X Lu, Y Hua, H Wei, H Jia - 2022 - pdfs.semanticscholar.org
Accurate valve flow rate prediction is essential for the flow control process of independent
metering (IM) hydraulic valve. Traditional estimation methods are difficult to meet the high …

[PDF][PDF] TECHNIQUES D'INTELLIGENCE ARTIFICIELLE DANS LA MODÉLISATION DU PROCESSUS ÉLECTROCHIMIQUE POUR LE TRAITEMENT DES EAUX …

MG Shirkoohi - 2022 - modeleau.fsg.ulaval.ca
Les technologies électrochimiques sont connues et utilisées pour le traitement des eaux
usées contenant des polluants organiques récalcitrants car les traitements conventionnels …

[PDF][PDF] Research Article Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three-Phase Power Transformer Winding Conductors

F Valencia, H Arcos, F Quilumba - 2021 - academia.edu
Research Article Comparison of Machine Learning Algorithms for the Prediction of Mechanical
Stress in Three-Phase Power Transfor Page 1 Research Article Comparison of Machine …