Details

Title

Genetic-fuzzy model of diesel engine working cycle

Journal title

Bulletin of the Polish Academy of Sciences: Technical Sciences

Yearbook

2010

Numer

No 4 December

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences

Date

2010

Identifier

ISSN 0239-7528, eISSN 2300-1917

References

Rychter T. (2006), Theory of Piston Engines. ; Amsden A. (1997), KIVA-3V: a Block-Structured KIVA Program for Engines with Vertical or Canted Valves. ; Gessing R. (2010), Whether the opinion about superiority of fuzzy controllers is justified, Bull. Pol. Ac.: Tech, 58, 1, 59. ; Witkowski T. (2009), Multi-objective decision making and search space for the evaluation of production process scheduling, Bull. Pol. Ac.: Tech, 57, 3, 195. ; Kalogirou S. (2003), Artificial intelligence for the modeling and control of combustion processes: a review, Progress in Energy and Combustion Science, 29, 515, doi.org/10.1016/S0360-1285(03)00058-3 ; Kimmich F. (2005), Fault detection for modern Diesel engines using signal- and process modelbased methods, Control Eng. Practice, 13, 189, doi.org/10.1016/j.conengprac.2004.03.002 ; Brzozowski K. (2005), An application of artificial neural network to exhaust emission modelling from diesel engine, J. KONES, 12, 1-2, 51. ; Jakubek S. (2006), A local neuro-fuzzy network for high-dimensional models and optimization, Eng. Applications of Artificial Intelligence, 19, 705, doi.org/10.1016/j.engappai.2005.12.014 ; Lee S. (2007), Fuzzy logic and neuro-fuzzy modelling of diesel spray penetration: a comparative study, J. Intelligent and Fuzzy Systems, 18, 1, 43. ; D. Kurczyński, "Influence of vegetable fuels and its blends with diesel oil on parameters of work of compression ignition engine", <i>PhD Thesis</i>, Kielce University of Technology, Kielce, 2007. ; M. Kekez, "Modeling of work of compression ignition internal combustion engine with use of artificial intelligence methods", <i>PhD Thesis</i>, Kielce University of Technology, Kielce, 2008. ; Cordon O. (2004), Ten years of genetic fuzzy systems: current framework and new trends, Fuzzy Sets and Systems, 141, 5, doi.org/10.1016/S0165-0114(03)00111-8 ; Cordon O. (2001), Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases (Advances in Fuzzy Systems - Applications and Theory 19).

DOI

10.2478/v10175-010-0071-x

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