AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Electricity

Showing 31 to 40 of 125 articles

Clear Filters

GADF-VGG16 based fault diagnosis method for HVDC transmission lines.

PloS one
Transmission lines are most prone to faults in the transmission system, so high-precision fault diagnosis is very important for quick troubleshooting. There are some problems in current intelligent fault diagnosis research methods, such as difficulty...

Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM.

Sensors (Basel, Switzerland)
Multistep power consumption forecasting is smart grid electricity management's most decisive problem. Moreover, it is vital to develop operational strategies for electricity management systems in smart cities for commercial and residential users. How...

K-Means Clustering and Bidirectional Long- and Short-Term Neural Networks for Predicting Performance Degradation Trends of Built-In Relays in Meters.

Sensors (Basel, Switzerland)
The built-in relay in a meter is a key control component of a smart meter, and its reliability determines whether the user can use electricity safely and smoothly. In this paper, the degradation characteristics of the arc-burning energy are enhanced ...

[Research and application of photovoltaic cell online monitoring system for animal robot stimulator].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Power supply plays a key role in ensuring animal robots to obtain effective stimulation. To extending the stimulating time, there is a need to apply photovoltaic cells and monitor their parameter variations, which can help operators to obtain the opt...

Individualized Short-Term Electric Load Forecasting Using Data-Driven Meta-Heuristic Method Based on LSTM Network.

Sensors (Basel, Switzerland)
Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units. Thus, it is imperative to present new incentive methods to motivate such power ...

An open-source deep learning model for predicting effluent concentration in capacitive deionization.

The Science of the total environment
To effectively evaluate the performance of capacitive deionization (CDI), an electrochemical ion separation technology, it is necessary to accurately estimate the number of ions removed (effluent concentration) according to energy consumption. Herein...

A Deep Learning Approach to Detect Anomalies in an Electric Power Steering System.

Sensors (Basel, Switzerland)
As anomaly detection for electrical power steering (EPS) systems has been centralized using model- and knowledge-based approaches, EPS system have become complex and more sophisticated, thereby requiring enhanced reliability and safety. Since most cu...

Thermographic Fault Diagnosis of Shaft of BLDC Motor.

Sensors (Basel, Switzerland)
A technique of thermographic fault diagnosis of the shaft of a BLDC (Brushless Direct Current Electric) motor is presented in this article. The technique works for the shivering of the thermal imaging camera in the range of 0-1.5 [m/s]. An electric s...

Optically addressable dielectric elastomer actuator arrays using embedded percolative networks of zinc oxide nanowires.

Materials horizons
Dielectric elastomer actuators (DEAs) are electrically driven soft actuators that generate fast and reversible deformations, enabling lightweight actuation of many novel soft robots and haptic devices. However, the high-voltage operation of DEAs comb...

Electric-field-coupled oscillators for collective electrochemical perception in biohybrid robotics.

Bioinspiration & biomimetics
This work explores the application of nonlinear oscillators coupled by an electric field in water, inspired by weakly electric fish. Such coupled oscillators operate in clear and colloidal (mud, bottom silt) water and represent a collective electroch...