This study proposes a novel method for designing prosthetic heart valves (PHVs) by combining machine learning (ML) with optimization algorithms. This approach aims to overcome the limitations of ...

Many controlled processes, such as biochemical ones, are repetitive, similar to batch-organized processes. They generate Optimal Control Problems (OCPs) solved by optimal controllers, which often ...

Abstract: This paper presents a study of different fuzzy neural network (FNN) learning control methods for brushless dc (BLDC) motor drives. The FNN combines fuzzy logic (FL) with the learning ...

School of Information Science and Engineering, Northeastern University, Shenyang 110819, China Liaoning Key Laboratory of Intelligent Diagnosis and Safety for Metallurgical Industry, Northeastern ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

Abstract: As the core equipment for AC/DC conversion in ultra-high voltage direct current (UHVDC) transmission systems, thyristor converter valves are the main source of losses in converter stations.

The fault diagnosis of the inverter is fundamental to energy intelligence. Due to the complex characteristics of the inverter (e.g., high-dimensional decision and poor stability), it is challenging to ...

In view of the dynamics of the dam safety monitoring data, the sensitivity to time and space, and the nonlinearity, it has been proposed to use the firefly algorithm to search to determine the delay ...

Opioid-induced respiratory depression (OIRD) is the direct cause of death from opioid overdose, which accounts for the current global opioid crisis. Here, we report that neurons expressing the ...

Previously, we found that in the mammalian retina, inhibitory inputs onto starburst amacrine cells (SACs) are required for robust direction selectivity of On-Off direction-selective ganglion cells (On ...