Three‐phase feeder parameter estimation using radial basis function neural networks and multi‐run optimisation method with bad data preparation

IET Generation Transmission & Distribution ◽

10.1049/gtd2.12310 ◽

2021 ◽

Author(s):

Nien‐Che Yang ◽

Rui Huang ◽

Mou‐Fa Guo

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

Radial Basis Function ◽

Basis Function ◽

Data Preparation ◽

Three Phase ◽

Radial Basis ◽

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Parameter Estimation of Solid Cylindrical Electromagnetic Actuator Using Radial Basis Function Neural Networks

Lecture Notes in Electrical Engineering - Microelectronics, Electromagnetics and Telecommunications ◽

10.1007/978-81-322-2728-1_31 ◽

2015 ◽

pp. 349-363 ◽

Author(s):

V. V. Kondaiah ◽

Jagu S. Rao ◽

V. V. Subba Rao

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

Radial Basis Function ◽

Basis Function ◽

Electromagnetic Actuator ◽

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Radial Basis Function and Multilayer Perceptron neural networks for sea water optically active parameter estimation in case II waters: A comparison

International Journal of Remote Sensing ◽

10.1080/0143116031000103781 ◽

2003 ◽

Vol 24 (20) ◽

pp. 3917-3931 ◽

Author(s):

G. Corsini ◽

M. Diani ◽

R. Grasso ◽

M. De Martino ◽

P. Mantero ◽

...

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

Radial Basis Function ◽

Basis Function ◽

Multilayer Perceptron ◽

Sea Water ◽

Optically Active ◽

Case Ii Waters ◽

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Detection of bearing defects in three-phase induction motors using Park’s transform and radial basis function neural networks

Sadhana ◽

10.1007/bf02703379 ◽

2006 ◽

Vol 31 (3) ◽

pp. 235-244 ◽

Author(s):

Izzet Y. Önel ◽

K. Burak Dalci ◽

İbrahim Senol

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Induction Motors ◽

Bearing Defects ◽

Three Phase ◽

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Distribution Feeder Parameter Estimation without Synchronized Phasor Measurement by using Radial Basis Function Neural Networks and Multi-run Optimization Method

IEEE Access ◽

10.1109/access.2021.3140123 ◽

2022 ◽

pp. 1-1

Author(s):

Nien-Che Yang ◽

Rui Huang ◽

Mou-Fa Guo

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

Radial Basis Function ◽

Basis Function ◽

Optimization Method ◽

Phasor Measurement ◽

Radial Basis ◽

Distribution Feeder ◽

Synchronized Phasor Measurement

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SSME parameter estimation using radial basis function neural networks

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) ◽

10.1109/icnn.1994.374774 ◽

2002 ◽

Author(s):

K.R. Wheeler ◽

A.P. Dhawan

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

Radial Basis Function ◽

Basis Function ◽

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Three‐phase AC/DC power‐flow for balanced/unbalanced microgrids including wind/solar, droop‐controlled and electronically‐coupled distributed energy resources using radial basis function neural networks

IET Power Electronics ◽

10.1049/iet-pel.2016.0010 ◽

2017 ◽

Vol 10 (3) ◽

pp. 313-328 ◽

Author(s):

Hamid Reza Baghaee ◽

Mojtaba Mirsalim ◽

Gevork B. Gharehpetian ◽

Heidar Ali Talebi

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Energy Resources ◽

Distributed Energy Resources ◽

Distributed Energy ◽

Dc Power ◽

Three Phase ◽

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A Study on Three Phase Partial Discharge Pattern Classification with the Aid of Optimized Polynomial Radial Basis Function Neural Networks

The Transactions of The Korean Institute of Electrical Engineers ◽

10.5370/kiee.2013.62.4.544 ◽

2013 ◽

Vol 62 (4) ◽

pp. 544-553

Author(s):

Sung-Kwun Oh ◽

Hyun-Ki Kim ◽

Jung-Tae Kim

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Pattern Classification ◽

Basis Function ◽

Partial Discharge ◽

Discharge Pattern ◽

Three Phase ◽

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Identification of Nonlinear Dynamical System Based on Raised-Cosine Radial Basis Function Neural Networks

Neural Processing Letters ◽

10.1007/s11063-020-10410-9 ◽

2021 ◽

Author(s):

Guo Luo ◽

Zhi Yang ◽

Choujun Zhan ◽

Qizhi Zhang

Keyword(s):

Dynamical System ◽

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

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New methods based on back propagation (BP) and radial basis function (RBF) artificial neural networks (ANNs) for predicting the occurrence of haloketones in tap water

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.145534 ◽

2021 ◽

Vol 772 ◽

pp. 145534 ◽

Author(s):

Ying Deng ◽

Xiaoling Zhou ◽

Jiao Shen ◽

Ge Xiao ◽

Huachang Hong ◽

...

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Tap Water ◽

Back Propagation ◽

New Methods ◽

Radial Basis ◽

Artificial Neural

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A Comparison Study on Shape Parameter Selection in Pattern Recognition by Radial Basis Function Neural Networks

Journal of Physics Conference Series ◽

10.1088/1742-6596/1921/1/012124 ◽

2021 ◽

Vol 1921 ◽

pp. 012124

Author(s):

S Tavaen ◽

S Kaennakham

Keyword(s):

Neural Networks ◽

Pattern Recognition ◽

Radial Basis Function ◽

Basis Function ◽

Shape Parameter ◽

Parameter Selection ◽

Comparison Study ◽

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