Simple Case Study on Radius of Radial Basis Function Network for Sequential Approximate Optimization
Radial basis function (RBF) networks are used for various research field. Especially, they make handling easy for classification and function approximation due to their mathematical form. Some parameters of an RBF network should be carefully selected to obtain good performance for a specific problem...
Main Author: | Yoshiaki Katada |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2017-11-01
|
Series: | SICE Journal of Control, Measurement, and System Integration |
Subjects: | |
Online Access: | http://dx.doi.org/10.9746/jcmsi.10.551 |
Similar Items
-
A Brand-New Simple, Fast, and Effective Residual-Based Method for Radial Basis Function Neural Networks Training
by: Lifei Sun, et al.
Published: (2023-01-01) -
Solving Fractional Order Differential Equations by Using Fractional Radial Basis Function Neural Network
by: Rana Javadi, et al.
Published: (2023-06-01) -
On the Approximation of a Nonlinear Biological Population Model Using Localized Radial Basis Function Method
by: Marjan Uddin, et al.
Published: (2019-05-01) -
Optimized Radial Basis Function Neural Network Based Intelligent Control Algorithm of Unmanned Surface Vehicles
by: Renqiang Wang, et al.
Published: (2020-03-01) -
Hardware radial basis function neural network automatic generation
by: Lucas Leiva, et al.
Published: (2011-04-01)