Machine learning and the renewable energy revolution: Exploring solar and wind energy solutions for a sustainable future including innovations in energy storage

ADA Bin Abu Sofian, HR Lim… - Sustainable …, 2024 - Wiley Online Library
This article evaluates the present global condition of solar and wind energy adoption and
explores their benefits and limitations in meeting energy needs. It examines the historical …

Prediction of voltage sag relative location with data-driven algorithms in distribution grid

Y Yalman, T Uyanık, İ Atlı, A Tan, KÇ Bayındır, Ö Karal… - Energies, 2022 - mdpi.com
Power quality (PQ) problems, including voltage sag, flicker, and harmonics, are the main
concerns for the grid operator. Among these disturbances, voltage sag, which affects the …

Prediction of Solar Energy Yield Based on Artificial Intelligence Techniques for the Ha'il Region, Saudi Arabia

L Kolsi, S Al-Dahidi, S Kamel, W Aich, S Boubaker… - Sustainability, 2022 - mdpi.com
In order to satisfy increasing energy demand and mitigate global warming worldwide, the
implementation of photovoltaic (PV) clean energy installations needs to become common …

IoT system for gluten prediction in flour samples using nirs technology, Deep and Machine Learning Techniques

O Jossa-Bastidas, AO Sanchez, L Bravo-Lamas… - Electronics, 2023 - mdpi.com
Gluten is a natural complex protein present in a variety of cereal grains, including species of
wheat, barley, rye, triticale, and oat cultivars. When someone suffering from celiac disease …

Detecting broken receiver tubes in CSP plants using intelligent sampling and dual loss

MA Pérez-Cutiño, J Valverde, JM Díaz-Báñez - Applied Intelligence, 2023 - Springer
Concentrated solar power (CSP) is one of the growing technologies that is leading the
process of change from fossil fuels to renewable energies for electricity production. The …

Comparison Analysis of Classification Model Performance in Lung Cancer Prediction Using Decision Tree, Naive Bayes, and Support Vector Machine

D Widyawati, A Faradibah… - Indonesian Journal of …, 2023 - jurnal.yoctobrain.org
This research aims to analyze the performance of three classification models, namely
Decision Tree Classifier, Support Vector Machine, and Naive Bayes Classifier, in predicting …

[HTML][HTML] Three novel machine learning-based adaptive controllers for a photovoltaic shunt active power filter performance enhancement

AA Jai, M Ouassaid - Scientific African, 2024 - Elsevier
This study develops three new machine learning-based algorithms using the SVR prediction
approach. The overall objective is to enhance the performance of the PV shunt active power …

Using Machine Learning for Analysis a Database Outdoor Monitoring of Photovoltaic System

H Hafdaoui, S Bouchakour… - International Journal of …, 2022 - publisher.uthm.edu.my
: In this paper we propose a new method for analyzing the performance of photovoltaic
system using classification, the monitoring of photovoltaic module (150 W) was controlled …

A Fault and Capacity Loss Prediction Method of Wind Power Station under Extreme Weather

L Li, Y Zhuo, W Meng, Z Chen… - Mathematical Problems in …, 2023 - Wiley Online Library
Extreme weather events can severely affect the operation and power generation of wind
farms and threaten the stability and safety of grids with high penetration of renewable …

Clasificación de la ocupación espectral para la toma de decisiones en redes inalámbricas cognitivas implementando extracción de características y aprendizaje …

DA Giral-Ramírez, CA Hernández… - Información …, 2022 - SciELO Chile
Este estudio analiza la clasificación de la ocupación espectral para la toma de decisiones a
través de la implementación de la extracción de características y de reglas de clasificación …