A survey on LoRa for smart agriculture: Current trends and future perspectives
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 …
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
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 …
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 …
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 …
elements (features) contribute to the forecasting process of the solar irradiation. These …
Assessing Machine Learning Approaches for Photovoltaic Energy Prediction in Sustainable Energy Systems
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 …
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
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 …
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
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 …
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
The transition to renewable energies, in particular wind power, is essential to meeting
environmental challenges and ensuring a sustainable future. Precise estimation of wind …
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 …
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 …
nowadays. With time, such techniques will play a massive role in almost all spheres of …