Titlebook: Neural Networks and Soft Computing; Proceedings of the S Leszek Rutkowski,Janusz Kacprzyk Conference proceedings 2003 Physica-Verlag Heidel

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A Hybrid Connectionist for Multiple Regressionf three components: (1) a neural network which is trained to fit the data samples; (2) a simple algorithm for splitting the input space of the data into subregions and (3) the traditional multiple regression technique for finding the coefficients of the regression lines. While neural networks work p

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Financial Fraud Identification Using MF-ARTMAP Neural Networkαsed on the expert knowledge with the aim to achieve the tool with highest classification accuracy. The fraud was characterized with 22 features and verbal features were encoded into numerical values to be able to used them in classification procedure. The results show that in case of sufficient data

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Radial Basis Function Neural Networks: Theory and Applicationsl approximation and Cover’s theorems are outlined that justify powerful RBF network capabilities in function approximation and data classification tasks. The methods for regularising RBF generated mappings are addressed also. Links of these networks to kernel regression methods, density estimation,

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Šarūnas Raudyse linked and interact with each other, they are described separately in this chapter. For each level of the system, the dominant failure modes are summarized, and where possible related models describing the degradation are discussed. The chapter is illustrated with pictures of failure modes and an