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Sep 20, 2024 ， Experimental results show that predicting hourly total energy consumption of a building using machine learning algorithms is successful with high performance.
Sep 14, 2024 ， The study focuses on implementing and evaluating energy consumption prediction models using algorithms like long short-term memory (LSTM), random forest, and ...
3 days ago ， It evaluates the application of machine learning in clustering buildings based on their thermal characteristics using energy data of different time intervals.
Oct 2, 2024 ， Five HEP models are created using dataset combinations and machine learning algorithms. Based on the MC dataset, the random forest provides the best prediction ...
Sep 26, 2024 ， In the wave energy field, ML and DL algorithms have been employed to perform predictions in the area, showing significant advantages in terms of execution time ...
Sep 17, 2024 ， From the results, the energy-data-driven model demonstrated superior performance in annual heating demand estimations, with errors of ‐2.5% compared to 14% and ...
Sep 18, 2024 ， This paper presents a comparative study for the most common Deep Learning (DL) and Machine Learning (ML) algorithms employed for short-term solar irradiance ...
Sep 27, 2024 ， An innovative machine learning approach is introduced for the purpose of estimating the initial cost required to construct a green structure that consumes no ...
Sep 30, 2024 ， We propose a machine learning framework for monitoring energy consumption in smart home devices. The proposed framework involves an anomaly detection module, ...
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2 days ago ， Abstract- This study analyzes the application of machine learning (ML) and deep learning (DL) models to forecast hourly national energy consumption.