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Clustering and Interpretability of Residential Electricity Demand Profiles

Author(s): Kallel S; Amayri M; Bouguila N;

Efficient energy management relies on uncovering meaningful consumption patterns from large-scale electricity load demand profiles. With the widespread adoption of sensor technologies such as smart meters and IoT-based monitoring systems, granular and real-time electricity usage data have become available, enabling deeper insights into consumption behavio ...

Article GUID: 40218540


Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting

Author(s): Ahmed U; Mahmood A; Khan AR; Kuhlmann L; Alimgeer KS; Razzaq S; Aziz I; Hammad A;

The transition to sustainable energy has become imperative due to the depletion of fossil fuels. Solar energy presents a viable alternative owing to its abundance and environmental benefits. However, the intermittent nature of solar energy requires accurate forecasting of solar irradiance (SI) for reliable operation of photovoltaics (PVs) integrated syste ...

Article GUID: 40185800


Novelty detection in rover-based planetary surface images using autoencoders

Author(s): Stefanuk B; Skonieczny K;

In the domain of planetary science, novelty detection is gaining attention because of the operational opportunities it offers, including annotated data products and downlink prioritization. Using a variational autoencoder (VAE), this work improves upon state-of-the-art novelty detection performance in the context of Martian exploration by > 7 % (measured ...

Article GUID: 36313243


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