Abstract
Intelligent information technologies help us to solve complex data mining problems and therefore they are of particular interest. However, a generation of a specific technology structure demands high skills of a developer and this process is time-consuming as well. In this paper, we present an automated integration of intelligent information technologies for complex systems modeling and classification. We consider such popular techniques as neural networks, fuzzy rules based systems and neuro-fuzzy systems as well as evolutionary algorithms for automated generation. We also propose a new idea of genetic programming application to the design of intelligent information technologies ensembles for effectiveness and reliability improvement.
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Shabalov, A., Semenkin, E., Galushin, P. (2012). Integration of Intelligent Information Technologies Ensembles for Modeling and Classification. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_33
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DOI: https://doi.org/10.1007/978-3-642-28942-2_33
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