Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/C0D48812-7B96-4475-A24D-E52514838DAA | ||
| Year | 2008 | ||
| Type of Item | Conference Poster | ||
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| Bibliographic Citation | N. matsatsinis,N. Loukeris.(2008).Radial basis functions networks to hybrid neuro-genetic RBFNs in financial evaluation of corporations.Presented at 12th WSEAS International Conference on computers.[online]/Available:http://www.wseas.us/e-library/conferences/2008/crete/Computers/127-computers.pdf | ||
| Appears in Collections |
Financial management maximise investors’ return, seeking for stocks with increasing expected corporate value. Hidden information is included in vast accounting data and financial indices that are available in international financial markets. Methods of Econometrics and Artificial Intelligence- mainly in the field of Neural Networks- provide classifications of companies regarding their economic health. Radial Basis Function networks are examined in a hybrid form of Neural Network optimised with Genetic Algorithms and in a regular Neural Net form, to determine efficient methods of Financial Analysis. The regular Radial Basis Function network with 3 layers, Genetic Algorithms in all the layers and Cross Validation is superior to all the neuro-genetic forms of RBF in Financial Analysis.
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