Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
[HTML][HTML] Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models
Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy
sources into the grid as it provides accurate and timely information on the expected output of …
sources into the grid as it provides accurate and timely information on the expected output of …
[HTML][HTML] ML-based energy management of water pum** systems for the application of peak shaving in small-scale islands
This study introduces an energy management method that smooths electricity consumption
and shaves peaks by scheduling the operating hours of water pum** stations in a smart …
and shaves peaks by scheduling the operating hours of water pum** stations in a smart …
An incremental learning framework for photovoltaic production and load forecasting in energy microgrids
Energy management is crucial for various activities in the energy sector, such as effective
exploitation of energy resources, reliability in supply, energy conservation, and integrated …
exploitation of energy resources, reliability in supply, energy conservation, and integrated …
Robust stacking ensemble model for darknet traffic classification under adversarial settings
Encrypted traffic tunnelled by Tor or VPN is referred to as darknet traffic. The ability to detect,
identify, and characterize darknet traffic is critical for detecting network traffic generated by a …
identify, and characterize darknet traffic is critical for detecting network traffic generated by a …
[HTML][HTML] Baseline energy modeling for improved measurement and verification through the use of ensemble artificial intelligence models
Accurate estimation of energy savings is crucial for the effective implementation of energy
conservation measures (ECMs). Simultaneously, the integration of Artificial Intelligence (AI) …
conservation measures (ECMs). Simultaneously, the integration of Artificial Intelligence (AI) …
Estimating the energy savings of energy efficiency actions with ensemble machine learning models
Energy efficiency financing is considered among the top priorities in the energy sector
among several stakeholders. In this context, accurately estimating the energy savings …
among several stakeholders. In this context, accurately estimating the energy savings …
A data-driven multicriteria decision making tool for assessing investments in energy efficiency
Mainstreaming energy efficiency financing has been considered a key priority during the last
decade among several stakeholders. The capability offered by Multicriteria Decision …
decade among several stakeholders. The capability offered by Multicriteria Decision …
Optimization on selecting XGBoost hyperparameters using meta‐learning
T Lima Marinho, DC do Nascimento… - Expert …, 2024 - Wiley Online Library
With computational evolution, there has been a growth in the number of machine learning
algorithms and they became more complex and robust. A greater challenge is upon faster …
algorithms and they became more complex and robust. A greater challenge is upon faster …
Predicting thermal comfort in buildings with machine learning and occupant feedback
P Skaloumpakas, E Sarmas, Z Mylona… - … on Metrology for …, 2023 - ieeexplore.ieee.org
This scientific paper discusses the importance of thermal comfort control in buildings for
providing high-quality working and living environments. The paper proposes a machine …
providing high-quality working and living environments. The paper proposes a machine …