Paper Title
Energy Consumption Analysis Via Different Machine Learning Algorithms
Abstract
The amount of energy used by buildings is increasing as a consequence of increased urbanization and social
advancement. Predicting a building's energy needs is essential for promoting sustainable growth and energy efficiency,
which in turn reduces energy costs and has a lesser impact on the environment. This research focuses on the topic of
applying deep learning (DL) techniques to forecast energy use across time series using actual data. The performance of
statistical and DL algorithms was evaluated using data collected in real time from a smart grid installed in an experimental
building. Usage of energy in ensemble and single situations was examined using well-known artificial intelligence techniques.
The models which combine prediction and optimization approaches, is examined in-depth. The thorough comparative analysis
demonstrated that the hybrid model was excellent in performance than the single and ensemble models in terms of accuracy.
These models are thought to be suitable for usage and accurate enough to provide predictions, which can help users plan
their energy management strategies.
Keywords - Energy consumption; Artificial intelligence; Data mining; Time-series forecasting; Machine learning;
Residential building
Author - Rwan Darwesh, Hakan Koyuncu
Published : Volume-10,Issue-7 ( Jul, 2023 )
DOIONLINE Number - IJAECS-IRAJ-DOIONLINE-20034
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Published on 2023-11-15 |
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