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Artificial intelligence optimisation of gas turbine systems

Identyfikatory
Warianty tytułu
Konferencja
8 Konferencja. Problemy Badawcze Energetyki Cieplnej. PBEC/sympozjum (VIII ; 11-14.12.2007 ; Warszawa, Polska)
Języki publikacji
EN
Abstrakty
EN
It is commonly accepted that inside the whole European Union within the next 15 years signiflcant investments are expected in both the electricity production as well as in energy transfers. Such investments will need the precise decision-making processes, supported with very versatile engineering tools. The major objective of this paper is to propose an application of a new methodology to design of power systems in a fuIly automatic way. The proposed methodology utilises the current artificial intelligence tools like genetic algorithm, artificial neural networks, expert systems, fuzzy logic toolbox, etc.
Rocznik
Strony
529--537
Opis fizyczny
Bibliogr. 13 poz., rys., tab.
Twórcy
autor
autor
autor
autor
autor
  • Institute of Thermal Technology, Silesian University of Technology
Bibliografia
  • [1] Melli R., Sciubba E., A prototype expert system for the conceptual synthesis of thermal process, Energy Conversion and Management 38 (1997), 1737-1749.
  • [2] Arabas J., Lectures on evolutionary Algorithms, Wydawnictwa Naukowo-Techniczne, Warszawa 2001, (in Polish).
  • [3] Goldberg D.E., Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, MA, 1989.
  • [4] Michalewicz Z., Genetic Algorithms + Data Structures = Evolutionary Programs, Springer Verlag, Berlin and New York, 1996.
  • [5] Białecki R.A., Burczyński T., Długosz A., Kuś W., Ostrowski Z.. Evolutionary shape optimization of thermoelastic bodies exchanging heat by convection and radiation Computer Methods in Applied Mechanics and Engineering 194(17), pp. 1839-1859, 2005.
  • [6] Melli R., Sciubba E., Artificial Intelligence in Thermal Systems Design: Concepts and Applications, Nova Science - Pergamon Press, 1998.
  • [7] Rutkowski L., New Soft Computing Techniques for System Modelling, Pattern Classification and Image Processing, Springer, Berlin - Tokyo 2004.
  • [8] Rutkowski L., Flexible Neuro - Fuzzy Systems, Kluwer Academic Publishers, Boston-London 2004.
  • [9] Baeck T., Fogel D.B., Michalewicz Z. (eds.), Handbook of evolutionary computations, Computation Intelligence Library, Institute of Physics Publishing, 1997.
  • [10] Behrens W., Hawranek P. M. Manual for the Preparation of Industrial Feasibility Studies. Warszawa: United Nations Industrial Development Organisation, 1993-2003.
  • [11] Klein S.A. Engineering Equation Solver, Copyright ©1992-2003, www.fChart.com.
  • [12] Szargut J., Ziębik A., Stanek W., Depletion of non-renewable exergy resources as a measure of the ecological cost. Energy Conversion and Management 43 (2002), 1149-1163.
  • [13] Horlock J.H., Advanced Gas Turbine Cycles. Elsevier Science, Amsterdam-Tokyo, 2003.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA5-0021-0016
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