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Model Predictive Control Using Artificial Neural Network for Power Converters
IEEE transactions on industrial electronics (1982. Print), 2021There has been an increasing interest in using model predictive control (MPC) for power electronic applications. However, the exponential increase in computational complexity and demand of computing resources hinders the practical adoption of this highly
Daming Wang +8 more
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Mathematical methods in the applied sciences, 2022
In recent years, statisticians have become more and more interested in the study of mixture models, especially in the last decade, without adequately considering the difficulty of modeling the reliability measures of mixture models using artificial ...
Anum Shafiq +4 more
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In recent years, statisticians have become more and more interested in the study of mixture models, especially in the last decade, without adequately considering the difficulty of modeling the reliability measures of mixture models using artificial ...
Anum Shafiq +4 more
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A Review of Activation Function for Artificial Neural Network
International Symposium on Applied Machine Intelligence and Informatics, 2020The activation function plays an important role in the training and the performance of an Artificial Neural Network. They provide the necessary non-linear properties to any Artificial Neural Network.
Andrinandrasana David Rasamoelina +2 more
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IEEE Transactions on Neural Networks and Learning Systems, 2020
The Levenberg–Marquardt and Newton are two algorithms that use the Hessian for the artificial neural network learning. In this article, we propose a modified Levenberg–Marquardt algorithm for the artificial neural network learning containing the training
José de Jesús Rubio
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The Levenberg–Marquardt and Newton are two algorithms that use the Hessian for the artificial neural network learning. In this article, we propose a modified Levenberg–Marquardt algorithm for the artificial neural network learning containing the training
José de Jesús Rubio
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Fault Detection Method based on Artificial Neural Network for 330kV Nigerian Transmission Line
International Journal of Innovative Science and Research TechnologyThis research focused on identifying various types of faults occurring on 330kV transmission lines through the use of artificial neural networks (ANN).
Alhassan Musa Oruma +5 more
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IEEE Transactions on Smart Grid, 2019
Ever-changing variables in the electricity market require energy management systems (EMSs) to make optimal real-time decisions adaptively. Demand response (DR) is the latest approach being used to accelerate the efficiency and stability of power systems.
Renzhi Lu, S. Hong, Mengmeng Yu
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Ever-changing variables in the electricity market require energy management systems (EMSs) to make optimal real-time decisions adaptively. Demand response (DR) is the latest approach being used to accelerate the efficiency and stability of power systems.
Renzhi Lu, S. Hong, Mengmeng Yu
semanticscholar +1 more source
A review of the artificial neural network surrogate modeling in aerodynamic design
Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2019Artificial neural network surrogate modeling with its economic computational consumption and accurate generalization capabilities offers a feasible approach to aerodynamic design in the field of rapid investigation of design space and optimal solution ...
Gang Sun, Shuyue Wang
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Unsupervised Learning Based On Artificial Neural Network: A Review
IEEE International Conference on Cyborg and Bionic Systems, 2018Artificial neural networks (ANN) have been applied effectively in numerous fields for the aim of prediction, knowledge discovery, classification, time series analysis, modeling, etc.
Happiness Ugochi Dike +3 more
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Bitcoin technical trading with artificial neural network
Physica A: Statistical Mechanics and its Applications, 2018This paper explores Bitcoin intraday technical trading based on artificial neural networks for the return prediction. In particular, our deep learning method successfully discovers trading signals through a seven layered neural network structure for ...
M. Nakano +2 more
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