Download Artificial Intelligence Applications and Innovations: IFIP by M. R. Gholamian, S. M. T. Fatemi Ghomi, M. Ghazanfari PDF

By M. R. Gholamian, S. M. T. Fatemi Ghomi, M. Ghazanfari (auth.), Daoliang Li, Baoji Wang (eds.)

International Federation for info Processing

The IFIP sequence publishes cutting-edge leads to the sciences and applied sciences of knowledge and communique. The scope of the sequence contains: foundations of desktop technological know-how; software program concept and perform; schooling; desktop functions in know-how; communique platforms; structures modeling and optimization; details platforms; desktops and society; desktops know-how; protection and security in info processing structures; man made intelligence; and human-computer interplay. court cases and post-proceedings of referred overseas meetings in desktop technological know-how and interdisciplinary fields are featured. those effects frequently precede magazine book and symbolize the most up-tp-date learn. The significant target of the IFIP sequence is to inspire schooling and the dissemination and alternate of knowledge approximately all elements of computing.

For additional info concerning the three hundred different books within the IFIP sequence, please stopover at

For additional info approximately IFIP, please stopover at

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Extra info for Artificial Intelligence Applications and Innovations: IFIP TC12 WG12.5 - Second IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI2005), September 7–9, 2005, Beijing, China

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3. 4324 where the n^ is compressor rotor speed, ni is fan rotor speed, mf is core fuel flow and Ae is nozzle throat area. The system matrices are determined by linearization of non-linear physical model around design condition of Mach 0 and 0-km altitude. For this application, the controller includes four fuzzy decoupling controllers and two fuzzy inverse models. 2 can be employed for both fuzzy inverse models and fuzzy decoupling controllers. 012]. The design condition simulation results for the adaptive fuzzy decoupling controller of the aero-engine are shown in Figure 3 for n^^ and Figure 4 for nj.

1997, 287-291. [16] Poulos PN, et al. A Pareto optimal genetic algorithm for warehouse multi-objective optimization. Engineering Applications of Artificial Intelligence, 2001, 14: 737-749 [17] Rasmy MH, et al. An expert system for multiobjective decision making: application of fuzzy linguistic preferences and goal programming. Fuzzy Sets and Systems, 2002, 127: 209-220. [18] Steuer PE, Multiple criteria optimization: theory, computation and application. John Wiley & Sons, New York, 1986 [19] Van Veldhauizen D, Lamont GB.

2001, Marcel Dekker Inc, New York. , Managing Engineering Knowledge: MOKA - Methodology for Knowledge Based Engineering Applications. 2001, London, UK: Professional Engineering and Publishing Limited. conceptual modelling of knowledge-based systems using uml 7. 8. 9. 10. 11. 12. 13. : Generating product configuration knowledge bases from precise domain extended UML models, in 12 th International Conference on Software Engineering and Knowledge Engineering (SEKE'OO). 2000. Chicago, USA. 4). 2001.

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