Abstract
The paper presents the design of municipal creditworthiness parameters. Further, a model is designed based on Learning Vector Quantization neural networks for municipal creditworthiness classification. The model is composed of Kohonen’s Self-organizing Feature Maps (unsupervised learning) whose outputs represent the input of the Learning Vector Quantization neural networks (supervised learning).
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Hájek, P., Olej, V. (2008). Municipal Creditworthiness Modelling by Kohonen’s Self-organizing Feature Maps and LVQ Neural Networks. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_6
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DOI: https://doi.org/10.1007/978-3-540-69731-2_6
Publisher Name: Springer, Berlin, Heidelberg
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