IJON
2006
13 years 4 months ago
2006
In this paper we propose a novel approach for modeling kernels in Radial Basis Function networks. The method provides an extra degree of flexibility to the kernel structure. This ...
IJON
2006
13 years 4 months ago
2006
This article presents a new system for automatically constructing and training radial basis function networks based on original evolutionary computing methods. This system, called...
CGF
2006
13 years 4 months ago
2006
Functional approximation of scattered data is a popular technique for compactly representing various types of datasets in computer graphics, including surface, volume, and vector ...
ENVSOFT
2008
13 years 4 months ago
2008
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
NCI
2004
13 years 6 months ago
2004
In the Neural Networks approach by Radial Basis Function - RBF, the property of interpolation between faces, their variation, and the diversity of faces helps to minimize the outp...
ESANN
2001
13 years 6 months ago
2001
Networks estimating probability density are usually based on radial basis function of the same type. Feature Space Mapping constructive network based on separable functions, optimi...
ACST
2006
13 years 6 months ago
2006
In the last years, there has been an increased investigation of efficient algorithms to solve problems of great scale. The main restriction of the traditional methods, like finite...
IADIS
2008
13 years 6 months ago
2008
After an oil spill it is essential to know if an area is going to be affected by the oil slicks generated. The system presented here forecasts the presence or not of oil slicks in...
ESANN
2008
13 years 6 months ago
2008
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
ESANN
2007
13 years 6 months ago
2007
Abstract. Using radial basis function networks for function approximation tasks suffers from unavailable knowledge about an adequate network size. In this work, a measuring techni...