On the Comparison of Fuzzy Kernel Regression Estimator and Fuzzy Radial Basis Function Networks

Pehlivan, Nimet Yapici; Apaydin, Aysen
July 2008
Gazi University Journal of Science;Jul2008, Vol. 21 Issue 3, p87
Academic Journal
No abstract available.


Related Articles

  • Forecasting Financial Time Series Using Multiple Regression, Multi Layer Perception, Radial Basis Function and Adaptive Neuro Fuzzy Inference System Models: A Comparative Analysis. Chaudhuri, Arindam // Computer & Information Science;Nov2012, Vol. 5 Issue 6, p13 

    In the last few decades, techniques such as Artificial Neural Networks and Fuzzy Inference Systems were used for developing predictive models to estimate the required parameters. Since the recent past Soft Computing techniques are being used as alternate statistical tool. Determination of nature...

  • Evaluation of Fuzzy Linear Regression Models by Parametric Distance. Saneifard, Rasoul // Australian Journal of Basic & Applied Sciences;2011, Vol. 5 Issue 3, p261 

    Fuzzy linear regression models can provide an estimated fuzzy number that has a fuzzy membership function. If a point that has the highest membership value from the estimated fuzzy number is not within the support of the observed fuzzy membership function, a decision maker can have high risk...

  • Direct Model Reference Adaptive Controller Based-On Neural-Fuzzy Techniques for Nonlinear Dynamical Systems. Husain, Hafizah; Khalid, Marzuki; Yusof, Rubiyah // American Journal of Applied Sciences;2008, Vol. 5 Issue 7, p769 

    This paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase,...

  • Radial tree-growth modelling with fuzzy regression. Boreux, J.J.; Gadbin-Henry, C.; Guiot, J.; Tessier, L. // Canadian Journal of Forest Research;Aug1998, Vol. 28 Issue 8, p1249 

    Investigates the radial tree-growth modelling with fuzzy regression. Description of fuzzy linear regression; Analysis of the response function of tree growth; Intervals of credibility given by the fuzzy regression.

  • Robust adaptive fuzzy neural tracking control for a class of unknown chaotic systems. KADIR, ABDURAHMAN; WANG, XING-YUAN; ZHAO, YU-ZHANG // Pramana: Journal of Physics;Jun2011, Vol. 76 Issue 6, p887 

    In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is proposed. The proposed AFNC is comprised of a fuzzy neural controller and a robust controller. The fuzzy neural controller including a fuzzy neural network identifier (FNNI) is the principal...

  • Forecasting High Frequency Data: An ARMA-Soft RBF Network Model for Time Series. Marcek, Dusan // Applied Mechanics & Materials;2014, Issue 596, p160 

    In the article we alternatively develop forecasting models based on the Box-Jenkins methodology and on the neural approach based on classic and fuzzy logic radial basis function neural networks. We evaluate statistical and neuronal forecasting models for monthly platinum price time series data....

  • Assessment of porosity using spatial correlation-based radial basis function and neuro-fuzzy inference system. Tutmez, Bulent // Neural Computing & Applications;Apr2010, Vol. 19 Issue 3, p499 

    Aquifer porosity indicates the storage groundwater capacity and groundwater quality. It may be measured via different techniques. This paper presents a novel spatial methodology based on radial basis function (RBF) and neuro-fuzzy inference system for modelling the porosity. Use of the point...

  • A Criterion for the Fuzzy Set Estimation of the Regression Function. Fajardo, Jesús A. // Journal of Probability & Statistics;2012, p1 

    We propose a criterion to estimate the regression function by means of a nonparametric and fuzzy set estimator of the Nadaraya-Watson type, for independent pairs of data, obtaining a reduction of the integrated mean square error of the fuzzy set estimator regarding the integrated mean square...

  • Probability propagation in fuzzy Bayesian belief networks with nondeterministic states. Verovka, O. V.; Parasyuk, I. N. // Cybernetics & Systems Analysis;Nov2008, Vol. 44 Issue 6, p925 

    The conceptual basis of fuzzy Bayesian belief networks with nondeterministic states is considered. The concept of a fuzzy probability estimate as a fuzzy relation of special type is introduced and its geometrical interpretation is given. Functional transformations of fuzzy probability estimates...

  • Componentwise Fuzzy Linear Regression Using Least Squares Estimation. JIN HEEYOON; SEUNG HOE CHOI // Journal of Multiple-Valued Logic & Soft Computing;2009, Vol. 15 Issue 2/3, p137 

    This paper introduces a component wise fuzzy linear regression model in order to construct a fuzzy relationship between fuzzy dependent and independent variables. We use the least squares method for an α-level set of observed fuzzy numbers in order to estimate the component wise fuzzy...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics