Physical systems that exhibit brain-like behaviour are currently under intense investigation as platforms for neuromorphic computing. We show that discontinuous metal films, comprising irregular flat islands on a substrate and formed using simple eva...
Soft-bodied aquatic invertebrates can overcome hydrodynamic resistance and display diverse locomotion modes in response to environmental cues. Exploring the dynamics of locomotion from bioinspired aquatic actuators will broaden the perspective of und...
IntelliSense fabrics that can sense transient mechanical stimuli are widely anticipated in flexible and wearable electronics. However, most IntelliSense fabrics developed so far are only sensitive to quasi-static forces, such as stretching, bending, ...
Detecting fraud related to electricity consumption is usually a difficult challenge as the input datasets are sometimes unreliable due to missing and inconsistent records, faults, misinterpretation of meter reading remarks, status, etc. In this paper...
Small (Weinheim an der Bergstrasse, Germany)
Feb 25, 2022
Piezoelectric pressure sensors are important for applications in robotics, artificial intelligence, communication devices, etc. The hyperboloid is theoretically predicted to be an unusual 3D structure that allows concerted piezoelectric enhancement o...
Computational intelligence and neuroscience
Feb 21, 2022
In the competitive electricity market, electricity price reflects the relationship between power supply and demand and plays an important role in the strategic behavior of market players. With the development of energy storage systems after watt-hour...
Structural health monitoring (SHM) in an electric arc furnace is performed in several ways. It depends on the kind of element or variable to monitor. For instance, the lining of these furnaces is made of refractory materials that can be worn out over...
Computational intelligence and neuroscience
Feb 8, 2022
Daily peak load forecasting (DPLF) and total daily load forecasting (TDLF) are essential for optimal power system operation from one day to one week later. This study develops a Cubist-based incremental learning model to perform accurate and interpre...
Nowadays, electric vehicles have gained great popularity due to their performance and efficiency. Investment in the development of this new technology is justified by increased consciousness of the environmental impacts caused by combustion vehicles ...
As artificial neural network architectures grow increasingly more efficient in time-series prediction tasks, their use for day-ahead electricity price and demand prediction, a task with very specific rules and highly volatile dataset values, grows mo...
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