AI Medical Compendium Topic

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

Electric Power Supplies

Showing 11 to 20 of 160 articles

Clear Filters

New approach for accurate discrimination and location of power transformers with different internal winding faults.

PloS one
Power transformers are essential elements in power systems and thus their protection schemes have critical importance. In this paper, a scheme is proposed for accurate discrimination and location of internal faults in power transformers using convent...

Novel glassbox based explainable boosting machine for fault detection in electrical power transmission system.

PloS one
The reliable operation of electrical power transmission systems is crucial for ensuring consumer's stable and uninterrupted electricity supply. Faults in electrical power transmission systems can lead to significant disruptions, economic losses, and ...

Machine-learning based control of bi-modular multilevel PWM inverter for high power applications.

PloS one
This paper presents the topology and machine learning-based intelligent control of high-power PV inverter for maximum power extraction and optimal energy utilization. Modular converters with reduced components economic and reliable for high power app...

Decoupling ion concentrations from effluent conductivity profiles in capacitive and battery electrode deionizations using an artificial intelligence model.

Water research
Owing to its simplicity of measurement, effluent conductivity is one of the most studied factors in evaluations of desalination performance based on the ion concentrations in various ion adsorption processes such as capacitive deionization (CDI) or b...

Research on short-term power load forecasting based on VMD and GRU.

PloS one
The traditional method for power load forecasting is susceptible to various factors, including holidays, seasonal variations, weather conditions, and more. These factors make it challenging to ensure the accuracy of forecasting results. Additionally,...

Ultralow-Power Single-Sensor-Based E-Nose System Powered by Duty Cycling and Deep Learning for Real-Time Gas Identification.

ACS sensors
This study presents a novel, ultralow-power single-sensor-based electronic nose (e-nose) system for real-time gas identification, distinguishing itself from conventional sensor-array-based e-nose systems, whose power consumption and cost increase wit...

Economic benefit analysis of lithium battery recycling based on machine learning algorithm.

PloS one
Lithium batteries, as an important energy storage device, are widely used in the fields of renewable vehicles and renewable energy. The related lithium battery recycling industry has also ushered in a golden period of development. However, the high c...

GraphKM: machine and deep learning for K prediction of wildtype and mutant enzymes.

BMC bioinformatics
Michaelis constant (K) is one of essential parameters for enzymes kinetics in the fields of protein engineering, enzyme engineering, and synthetic biology. As overwhelming experimental measurements of K are difficult and time-consuming, prediction of...

Small object detection algorithm incorporating swin transformer for tea buds.

PloS one
Accurate identification of small tea buds is a key technology for tea harvesting robots, which directly affects tea quality and yield. However, due to the complexity of the tea plantation environment and the diversity of tea buds, accurate identifica...

Advancing mortality rate prediction in European population clusters: integrating deep learning and multiscale analysis.

Scientific reports
Accurately predicting population mortality rates is crucial for effective retirement insurance and economic policy formulation. Recent advancements in deep learning time series forecasting (DLTSF) have led to improved mortality rate predictions compa...