Search Results - subject:"radial basis function"

Predicting credit card customer churn in banks using data mining

Kumar, Dudyala Anil; Ravi, V. - In: International Journal of Data Analysis Techniques and … 1 (2008) 1, pp. 4-28

Forest (RF), Radial Basis Function (RBF) network and Support Vector Machine (SVM) as the constituents. The dataset was taken …

Persistent link: https://www.econbiz.de/10008563411

A rating model simulation for risk analysis

Falavigna, Greta - In: International Journal of Business Performance Management 10 (2008) 2/3, pp. 269-299

This study analyses the situation of a bank that wants to create an Internal Rating System (IRB). A credit institute can decide to simulate rating judgements from an external rating agency, like Standard and Poor's or Moody's or Fitch Rating. This research compares different frameworks of neural...

Persistent link: https://www.econbiz.de/10010669374

Neural network-based mean-variance-skewness model for portfolio selection

Yu, Lean; Wang, Shouyang; Lai, Kin Keung - In: Computers & operations research : and their … 35 (2008) 1, pp. 34-46

Persistent link: https://www.econbiz.de/10003665721

An adaptive artificial neural network model for sizing stand-alone photovoltaic systems: application for isolated sites in Algeria

Mellit, A.; Benghanem, M.; Arab, A. Hadj; Guessoum, A. - In: Renewable Energy 30 (2005) 10, pp. 1501-1524

-numerical, B-spline function) and new models like feed-forward (MLP), radial basis function (RBF), MLP-IIR and RBF-IIR are compared … Basis Function (RBF) network and Infinite Impulse Response (IIR) filter in order to accelerate the convergence of the … suitable model for sizing Stand-Alone Photovoltaic (SAPV) systems, based on a minimum of input data. The model combines Radial …

Persistent link: https://www.econbiz.de/10010806568

Greenhouse temperature modeling: a comparison between sigmoid neural networks and hybrid models

Linker, Raphael; Seginer, Ido - In: Mathematics and Computers in Simulation (MATCOM) 65 (2004) 1, pp. 19-29

Greenhouse operation and inside climate strongly depend on the outside weather. This implies that at least a year of data collection is required to cover the whole operational domain. Greenhouse-climate models calibrated with data limited to only a small region of the operating domain (weather...

Persistent link: https://www.econbiz.de/10010748955

On-line RBFNN based identification of rapidly time-varying nonlinear systems with optimal structure-adaptation

Apostolikas, Giorgos; Tzafestas, Spyros - In: Mathematics and Computers in Simulation (MATCOM) 63 (2003) 1, pp. 1-13

This paper presents an adaptive RBF network for the on-line identification and tracking of rapidly-changing time-varying nonlinear systems. The proposed algorithm is capable of maintaining the accuracy of learned patterns even when a large number of aged patterns are replaced by new ones through...

Persistent link: https://www.econbiz.de/10010749526

A simple efficient algorithm for interpolation between different grids in both 2D and 3D

Li, Jichun; Chen, C.S. - In: Mathematics and Computers in Simulation (MATCOM) 58 (2002) 2, pp. 125-132

Considering the importance of data transferring between different grids, we present a simple but powerful interpolation scheme using radial basis functions (RBFs) to accomplish such task in both 2D and 3D. Numerical results are presented for such interpolation between truly unstructured grids.

Persistent link: https://www.econbiz.de/10010749120

Adaptive self-tuning neurocontrol

Potočnik, Primož; Grabec, Igor - In: Mathematics and Computers in Simulation (MATCOM) 51 (2000) 3, pp. 201-207

are implemented together in a single radial basis function network. The learning method involves structural adaptation …

Persistent link: https://www.econbiz.de/10011050452

Geometric selection of centers for radial basis function approximations involved in intensive computer simulations

Valdés, J.L.; Biscay, R.; Jimenez, J.C. - In: Mathematics and Computers in Simulation (MATCOM) 48 (1999) 3, pp. 295-306

A method for the selection of centers for radial basis function (RBF) approximation is introduced, which reduces the …

Persistent link: https://www.econbiz.de/10010748442