Artifical Intelligence and Soft Computing: 10th - download pdf or read online

By Igor Aizenberg (auth.), Leszek Rutkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)

ISBN-10: 3642132316

ISBN-13: 9783642132315

ISBN-10: 3642132324

ISBN-13: 9783642132322

This quantity constitutes the lawsuits of the tenth foreign convention on man made Intelligence and smooth Computing, ICAISC’2010, held in Zakopane, Poland in June 13-17, 2010. The articles are prepared in topical sections on Fuzzy platforms and Their purposes; facts Mining, class and Forecasting; snapshot and Speech research; Bioinformatics and clinical purposes (Volume 6113) including Neural Networks and Their purposes; Evolutionary Algorithms and Their purposes; Agent procedure, Robotics and keep an eye on; a variety of difficulties aof synthetic Intelligence (Volume 6114).

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Additional resources for Artifical Intelligence and Soft Computing: 10th International Conference, ICAISC 2010, Zakopane, Poland, June 13-17, 2010, Part II

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L. Rutkowski et al. ): ICAISC 2010, Part II, LNAI 6114, pp. 11–18, 2010. c Springer-Verlag Berlin Heidelberg 2010 12 T. Barszcz, A. Bielecki, and M. W´ ojcik the unit for wind energy is significantly different from that of traditional, fossil fired units [2]. First of all, initial investment costs are relatively higher, whereas in traditional units cost of fuel plays important role (usually it is the second largest cost). After commissioning, the largest cost for the wind turbine (WT for abbreviation) is maintenance.

Applied Optics 26, 4919–4930 (1987) 5. : Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks 4, 759–771 (1991) 6. : Performance evaluation for classification methods: A comparative simulation study. Expert Systems with Applications 37, 2292–2306 (2010) 7. : Artificial Intelligence Methods Applications in Manufacturing Engineering. WNT, Warsaw (2002) (in Polish) 8. : Artificial Neural Networks. Foundations and Applications. Academic Press PLJ, Warsaw (1994) (in Polish) 9.

The neural networks permit to build a global model because an internal structure of the complex model is adequate to the complex system. The learning process of neural networks allows to achieve satisfactory parameters of a global model for which the quality of model is good sufficiently. Complex systems can have varied structure [1] ,[2], [6]. In the paper a complex system is cascade connected simple plants, which is often present in industrial plants. 1 Global Modeling In global modeling global models have the same structure as complex systems and parameters of global models are sought.

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Artifical Intelligence and Soft Computing: 10th International Conference, ICAISC 2010, Zakopane, Poland, June 13-17, 2010, Part II by Igor Aizenberg (auth.), Leszek Rutkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)


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