AIMC Topic: Electricity

Clear Filters Showing 61 to 70 of 134 articles

Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion.

Sensors (Basel, Switzerland)
Only with new sensor concepts in a network, which go far beyond what the current state-of-the-art can offer, can current and future requirements for flexibility, safety, and security be met. The combination of data from many sensors allows a richer r...

Short-Term Demand Forecasting Method in Power Markets Based on the KSVM-TCN-GBRT.

Computational intelligence and neuroscience
With the consumption of new energy and the variability of user activity, accurate and fast demand forecasting plays a crucial role in modern power markets. This paper considers the correlation between temperature, wind speed, and real-time electricit...

Neuromorphic behaviour in discontinuous metal films.

Nanoscale horizons
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...

Electrically Controlled Aquatic Soft Actuators with Desynchronized Actuation and Light-Mediated Reciprocal Locomotion.

ACS applied materials & interfaces
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...

Electroassisted Core-Spun Triboelectric Nanogenerator Fabrics for IntelliSense and Artificial Intelligence Perception.

ACS nano
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, ...

Feature engineering solution with structured query language analytic functions in detecting electricity frauds using machine learning.

Scientific reports
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...

Electrohydrodynamic Pulling Consolidated High-Efficiency 3D Printing to Architect Unusual Self-Polarized β-PVDF Arrays for Advanced Piezoelectric Sensing.

Small (Weinheim an der Bergstrasse, Germany)
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...

Operational Scheduling of Behind-the-Meter Storage Systems Based on Multiple Nonstationary Decomposition and Deep Convolutional Neural Network for Price Forecasting.

Computational intelligence and neuroscience
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...

Attention-Based Deep Recurrent Neural Network to Forecast the Temperature Behavior of an Electric Arc Furnace Side-Wall.

Sensors (Basel, Switzerland)
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...

Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist.

Computational intelligence and neuroscience
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...