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 ...
Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. With the ...
Heat transfer, encompassing conduction, convection, and radiation, is a fundamental physical process critical to engineering, environmental science, and materials development. Modeling heat transfer ...
Recently, a research team led by Prof. GAO Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, developed an intelligent neural network algorithm that effectively ...
Abstract: For the high performance drives of induction motor, recurrent artificial neural network (RNN) based self tuning speed controller is proposed. RNN provides a nonlinear modeling of motor drive ...
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 ...
Solar energy serves as a great alternative to fossil fuels as they are clean and renewable energy. Accurate solar radiation (SR) prediction can substantially lower down the impact cost pertaining to ...
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 ...
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 ...
Cardiovascular diseases (CVDs) have become the number 1 threat to human health. Their numerous complications mean that many countries remain unable to prevent the rapid growth of such diseases, ...
Artificial neural network is an efficient and accurate fitting method. It has the function of self-learning, which is particularly important for prediction, and it could take advantage of the computer ...
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