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Radial Basis Function Neural Network (RBF-NN) Implementation

This project implements a Radial Basis Function Neural Network with Gaussian kernel function and constant spread function. The implementation uses all points in the input as centers for the Radial ...
Risk

A k-means++-improved radial basis function neural network model for corporate financial crisis early warning: an empirical model validation for Chinese listed companies

An early warning of corporate financial crises has long been the focus of investors and enterprises. Integrated early warning models for financial crises perform better than normal models, but most ...
JSTOR Daily

Stock price trend prediction using Bayesian regularised radial basis function network model

This paper introduces Bayesian regularised radial basis function network (BR-RBFN) as a novel approach to capture the 1-day daily future stock price movement. Naturally, the existence of prolonged ...
IEEE

A statistic comparison between radial basis function neural network and backpropagation neural network in die casting process modeling

Abstract: Nowadays, given its characteristics, the casting process is one of the most important manufacturing processes in the automotive industry. However, with the advancement of new technologies ...
IEEE

Euclidean distance and second derivative based widths optimization of radial basis function neural networks

Abstract: The design of radial basis function widths of Radial Basis Function Neural Network (RBFNN) is thoroughly studied in this paper. Firstly, the influence of the widths on performance of RBFNN ...
JSTOR Daily

MRI segmentation using Fuzzy C-means and radial basis function neural networks

Image segmentation is one of the major preprocessing steps of magnetic resonance imaging (MRI) analysis in many medical and research applications. Accurate differentiation between three major soft ...