A survey on LoRa for smart agriculture: Current trends and future perspectives

A Pagano, D Croce, I Tinnirello… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
This article provides a survey on the adoption of LoRa in the agricultural field and reviews
state-of-the-art solutions for smart agriculture, analyzing the potential of this technology in …

Solar radiation forecasting by pearson correlation using LSTM neural network and ANFIS method: application in the west-central Jordan

H Fraihat, AA Almbaideen, A Al-Odienat, B Al-Naami… - Future Internet, 2022 - mdpi.com
Solar energy is one of the most important renewable energies, with many advantages over
other sources. Many parameters affect the electricity generation from solar plants. This paper …

The solar energy forecasting using LSTM deep learning technique

TM Al-Jaafreh, A Al-Odienat… - … on Emerging Trends in …, 2022 - ieeexplore.ieee.org
The future power systems will be characterized by high penetration or even dominance of
renewable energy sources. This will present a challenge for the power system operators …

The Application of Deep Learning Techniques for Solar Power Forecasting

TM Al-Jaafreh, A Al-Odienat - 2022 13th International …, 2022 - ieeexplore.ieee.org
The future forecasting of the solar irradiation is becoming very essential. There are other
elements (features) contribute to the forecasting process of the solar irradiation. These …

Assessing Machine Learning Approaches for Photovoltaic Energy Prediction in Sustainable Energy Systems

M Abdelsattar, MA Ismeil, MA Azim… - IEEE …, 2024 - ieeexplore.ieee.org
Precise forecasting of solar power output is crucial for integrating renewable energy into
power networks, improving efficiency and dependability. This study assesses the efficacy of …

Optimization of photovoltaic installation based on machine learning for water pumping system using a BLDC motor

M Mostefai, M Sekour, M Amara - Journal of Electrical Engineering & …, 2023 - Springer
The photovoltaic system has abundant potential and is currently used more than other
renewable energy sources. However, the PV system may not perform optimally due to its …

Utilizing Machine Learning to Predict Offshore Wind Farm Power Output for European Countries

O Ozturk, B Hangun… - 2022 11th International …, 2022 - ieeexplore.ieee.org
One might assume that the types of energy resources used by a country and its level of
development are related since developed nations focus on using alternative energy sources …

Combination of Metaheuristic Algorithm and Artificial Neural Networks Model to Forecast Wind Energy

D Bouabdallaoui, T Haidi, EM Mellouli… - … Research in Applied …, 2024 - ieeexplore.ieee.org
The transition to renewable energies, in particular wind power, is essential to meeting
environmental challenges and ensuring a sustainable future. Precise estimation of wind …

Analysis of a Wind Speed Prediction Model Based on Decision Trees

JC Cruz, DQ Oliveira, FLA Neto… - 2023 Workshop on …, 2023 - ieeexplore.ieee.org
Predicting wind speed is crucial for efficient wind farm management, aiming to optimize en-
ergy production and ensure grid stability. This paper addresses wind speed prediction using …

Emerging role of AI, ML and IoT in modern sustainable energy management

A Tewary, C Upadhyay, AK Singh - IoT and Analytics in Renewable … - taylorfrancis.com
The relevance of modern computing tools and techniques is becoming quite significant
nowadays. With time, such techniques will play a massive role in almost all spheres of …