Investigation and Comparison of Generalization Ability of Multi-Layer Perceptron and Radial Basis Function Artificial Neural Networks for Signal Power Loss Prediction

Radial Basis Function ◽

Basis Function ◽

Power Loss ◽

Signal Power ◽

Multi Layer Perceptron ◽

Generalization Ability ◽

Loss Prediction ◽

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

Process Safety and Environmental Protection ◽

10.1016/j.psep.2014.04.006 ◽

2015 ◽

Vol 93 ◽

pp. 111-123 ◽

Cited By ~ 31

Author(s):

Majid Bagheri ◽

S.A. Mirbagheri ◽

Majid Ehteshami ◽

Zahra Bagheri

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Sequencing Batch Reactor ◽

Municipal Wastewater ◽

Batch Reactor ◽

Multi Layer Perceptron ◽

Radial Basis ◽

On Various Multi-Layer Perceptron and Radial Basis Function Based Artificial Neural Networks in the Process of a Hot Flow Curve Description

Journal of Materials Research and Technology ◽

10.1016/j.jmrt.2021.07.100 ◽

2021 ◽

Author(s):

Petr Opěla ◽

Ivo Schindler ◽

Petr Kawulok ◽

Rostislav Kawulok ◽

Stanislav Rusz ◽

...

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Flow Curve ◽

Multi Layer Perceptron ◽

Radial Basis ◽

2017 IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON) ◽

Signal power loss prediction based on artificial neural networks in microcell environment

10.1109/nigercon.2017.8281897 ◽

2017 ◽

Author(s):

Virginia Chika Ebhota ◽

Joseph Isabona ◽

Viranjay M. Srivastava

Keyword(s):

Neural Networks ◽

Power Loss ◽

Signal Power ◽

Loss Prediction ◽

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 ◽

Cited By ~ 2

Author(s):

Ying Deng ◽

Xiaoling Zhou ◽

Jiao Shen ◽

Ge Xiao ◽

Huachang Hong ◽

...

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Tap Water ◽

Back Propagation ◽

New Methods ◽

Radial Basis ◽

Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286) ◽

Pre- and post-operative predictions of recurrence in patients with cancer of the oesophago-gastric junction using radial basis function artificial neural networks

10.1109/iembs.1998.746214 ◽

2002 ◽

Author(s):

R.N.G. Naguib ◽

J. Wayman ◽

M.K. Bennett ◽

S.A. Raimes ◽

S.M. Griffin

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Patients With Cancer ◽

Radial Basis ◽

Centre and Variance Selection for Gaussian Radial Basis Function Artificial Neural Networks

Artificial Neural Nets and Genetic Algorithms ◽

10.1007/978-3-7091-6384-9_25 ◽

1999 ◽

pp. 141-147

Author(s):

F. Scheibel ◽

N. C. Steele ◽

R. Low

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Radial Basis ◽

Selection For ◽

Artificial neural networks in structural dynamics: A new modular radial basis function approach vs. convolutional and feedforward topologies

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2020.112989 ◽

2020 ◽

Vol 364 ◽

pp. 112989 ◽

Cited By ~ 3

Author(s):

Marcus Stoffel ◽

Rutwik Gulakala ◽

Franz Bamer ◽

Bernd Markert

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Structural Dynamics ◽

Basis Function ◽

Function Approach ◽

Radial Basis ◽

An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

Educational Sciences Theory & Practice ◽

10.12738/estp.2015.5.0238 ◽

2015 ◽

Cited By ~ 6

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Multilayer Perceptron ◽

Performance Comparison ◽

Radial Basis ◽

Artificial Neural ◽

Intelligent Approach

Landslide Hazard Zonation in Taleghan watershed by using intelligent systems (Gaussian radial basis function and multilayer perceptron artificial neural networks)

Journal of Engineering Geology ◽

10.18869/acadpub.jeg.10.3.3601 ◽

2017 ◽

Vol 10 (3) ◽

pp. 3601-3626

Author(s):

N Salimi ◽

M FatemiAghda ◽

M Teshnehlab ◽

Y Sharafi ◽

◽

...

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Multilayer Perceptron ◽

Intelligent Systems ◽

Landslide Hazard ◽

Hazard Zonation ◽

Landslide Hazard Zonation ◽

Prediction of Coral South FLNG Side-by-Side Offloading Operability Using Radial Basis Function Artificial Neural Networks

10.4043/29263-ms ◽

2019 ◽

Cited By ~ 1

Author(s):

Erwan Auburtin ◽

Thiago Miliante ◽

Diego Lima

Keyword(s):

Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Radial Basis ◽