[HTML][HTML] A Comparative Study of Machine Learning Models for Predicting Meteorological Data in Agricultural Applications
This study aims to address the challenges of climate change, which has led to extreme
temperature events and reduced rainfall, using Internet of Things (IoT) technologies …
temperature events and reduced rainfall, using Internet of Things (IoT) technologies …
[HTML][HTML] Application of wavelet and seasonal-based emotional ANN (EANN) models to predict solar irradiance
This study models solar irradiance at six stations in Iran and the USA on an hourly scale. We
explored two seasonal emotional artificial neural networks (EANN): sequence-EANN …
explored two seasonal emotional artificial neural networks (EANN): sequence-EANN …
[HTML][HTML] Accurate Method for Solar Power Generation Estimation for Different PV (Photovoltaic Panels) Technologies
In 2023, solar photovoltaic energy alone accounted for 75% of the global increase in
renewable capacity. Moreover, this natural energy resource is the one that requires the least …
renewable capacity. Moreover, this natural energy resource is the one that requires the least …
[HTML][HTML] Analyzing the impact of temperature on PV module surface during electricity generation using machine learning models
Use of fossil fuel in industries causes Carbon emission, which is mostly responsible for
global warming. Another aspect is that environment friendly energy production and …
global warming. Another aspect is that environment friendly energy production and …
[HTML][HTML] High-resolution working layouts and time series for renewable energy generation in Europe
The stability and manageability of power systems with a growing share of renewable
energies depend on accurate forecasts and feed-in information. This study provides …
energies depend on accurate forecasts and feed-in information. This study provides …
[PDF][PDF] Performance Evaluation of Photovoltaic Panels in Extreme Environments: A Machine Learning Approach on Horseshoe Island, Antarctica. Sustainability 2025 …
Due to the supply problems of fossil-based energy sources, the tendency towards alternative
energy sources is relatively high. For this reason, the use of solar energy systems is …
energy sources is relatively high. For this reason, the use of solar energy systems is …
Enhanced accuracy in solar irradiance forecasting through machine learning stack-based ensemble approach
Accurate solar irradiance (SI) prediction is vital for optimizing solar photovoltaic systems.
This study addresses shortcomings in existing forecasting methods by exploring advanced …
This study addresses shortcomings in existing forecasting methods by exploring advanced …
[HTML][HTML] Generalizable Solar Irradiance Prediction for Battery Operation Optimization in IoT-Based Microgrid Environments
R Colucci, I Mahgoub - Journal of Sensor and Actuator Networks, 2024 - mdpi.com
The reliance on fossil fuels as a primary global energy source has significantly impacted the
environment, contributing to pollution and climate change. A shift towards renewable energy …
environment, contributing to pollution and climate change. A shift towards renewable energy …
[HTML][HTML] Prediction of solar radiation as a function of particulate matter pollution and meteorological data using machine learning models
SM Aladwani, A Almutairi, MA Alolayan… - Journal of Engineering …, 2024 - Elsevier
A clear understanding of global solar radiation data-based location is required for designing
efficient solar energy systems less affected by environmental and meteorological conditions …
efficient solar energy systems less affected by environmental and meteorological conditions …
Short-Term Photovoltaic System Output Power Prediction Based on Integrated Deep Learning Algorithms in the Clean Energy Sector
R Wang, X Liu, Y Chang, D Liu, H Yao - International Journal of e …, 2024 - igi-global.com
Photovoltaic power generation system plays an important role in renewable energy.
Therefore, accurately predicting the short-term output power of photovoltaic system has …
Therefore, accurately predicting the short-term output power of photovoltaic system has …