Application of random forest, radial basis function neural networks and central composite design for modeling and/or optimization of the ultrasonic assisted adsorption of brilliant green on ZnS-NP-AC

2017 ◽  
Vol 505 ◽  
pp. 278-292 ◽  
Author(s):  
M.H. Ahmadi Azqhandi ◽  
M. Ghaedi ◽  
F. Yousefi ◽  
M. Jamshidi
Keyword(s):  
Neural Networks ◽  
Random Forest ◽  
Central Composite Design ◽  
Radial Basis Function ◽  
Basis Function ◽  
Brilliant Green ◽  
Radial Basis ◽  
Ultrasonic Assisted ◽  
Central Composite

Type-2 Radial Basis Function Neural Networks Mandami System to Evaluate Quality Features

2021 ◽  
Author(s):  
Pascual Noradino Montes Dorantes ◽  
Gerardo Maximiliano Méndez ◽  
Marco Aurelio Jiménez Gómez ◽  
Adriana Mexicano Santoyo
Keyword(s):  
Neural Networks ◽  
Central Composite Design ◽  
Radial Basis Function ◽  
Basis Function ◽  
Radial Basis ◽  
Interval Type ◽  
Central Composite ◽  
Quality Features

Abstract This paper presents type-1 and type-2 radial basis function networks to evaluate quality features. The proposed methodology fuses the central composite design and the radial basis function neural networks in type-1 or interval type-2 model to generate a network that evaluates quality features in an industrial image processing. The advantages of this proposal include that training is not required to get an accurate result and that the generation of the fuzzy rule base using central composite design method and statistical indicators is simplified. Another advantage is the excellent results obtained with the proposal. Experimentation shows an error reduction of 90% when the interval type 2 Mandami Radial basis function neural network compared against its type-1 counterpart using the Gaussian membership functions onto a radial basis function network.

Wind turbine power curve modeling using radial basis function neural networks and tabu search

2021 ◽  
Vol 163 ◽  
pp. 2137-2152
Author(s):  
Despina Karamichailidou ◽  
Vasiliki Kaloutsa ◽  
Alex Alexandridis
Keyword(s):  
Neural Networks ◽  
Tabu Search ◽  
Radial Basis Function ◽  
Wind Turbine ◽  
Basis Function ◽  
Power Curve ◽  
Radial Basis ◽  
Curve Modeling

Modeling and prediction of viscosity of water-based nanofluids by radial basis function neural networks

2015 ◽  
Vol 281 ◽  
pp. 173-183 ◽  
Author(s):  
Ningbo Zhao ◽  
Xueyou Wen ◽  
Jialong Yang ◽  
Shuying Li ◽  
Zhitao Wang
Keyword(s):  
Neural Networks ◽  
Radial Basis Function ◽  
Basis Function ◽  
Modeling And Prediction ◽  
Water Based ◽  
Radial Basis
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