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The smart power grid is a synergistic system that integrates diverse network components for power generation, transmission, and distribution. Its advanced metering infrastructure (AMI) enables the grid's efficient and reliable operation. Nevertheless, it is amenable to advanced cyber threats; malicious actors can compromise vulnerable meters and arbitrarily alter their readings. These orchestrated...
Occupant presence and behaviour have a large impact on building energy performance. With the availability of low cost and affordable sensors, accurate occupancy detection by combining sensor stream data with machine learning approaches becomes possible. In this paper, we propose a novel dynamical hidden semi-Markov model (D-HSMM) which can accurately detect occupancy pattern from sensor data stream...
Traffic flow cannot be predicted solely based on historical data due to its high dynamics and sensitivity to emergency situations. In this paper, a real traffic data collected from 2011 to 2014 is used, and an adaptive prediction model based on a variant of Extreme Learning Machine (ELM), namely On-line Sequential ELM with forgetting mechanism, is built. The model has the capability of updating itself...
BIPV market is growing fast and contributing to zero-energy buildings. Installing PV systems on walls is unusual, however it has a huge potential to stimulate zero-energy buildings. The production of energy from photovoltaic panels installed vertically is difficult to predict due to some reasons like the interference of shadows caused by nearby buildings or adjacent vegetation, and the lower yield...
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