Scientific and Technical Journal

ELECTROTECHNIC AND COMPUTER SYSTEMS

ISSN Print 2221-3937
ISSN Online 2221-3805
MECHANISM OF TWO-STAGED CORRECTION AND ANALYSIS OF METHODS FOR RULE BASES OF FUZZY DECISION MAKING MODELS REDUCTION
Abstract:

In the work analyzed the existing methods for reduction of rule bases fuzzy models for decision support.There was developed the method, which allows for reduction the structure of rule bases fuzzy model for decision support. At the same time automates the setting consequent of rules by changing the input vector coordinates. Simulation results confirm the effectiveness and appropriateness of using the method of two-staged correction of rule bases fuzzymodels in multidimensional DSS.

Authors:
Keywords
DOI
References

References

  1. Altunin,А. Е. Models and algorithms for decision making in fuzzy terms: monographs / А. Е. Altunin, М. V. Semuhin. – Tuyman : Tyuman state university, 2000. – 352 p.[in Russian].
  2. Kondratenko, V. Yu. Object-oriented models for synthesis intelligent fuzzy systems / V. Yu. Kondratenko, V. S. Yatsenko // Proceedings ONPU. – 2006. – P. 54 – 60 [in Ukrainian].
  3. Kondratenko, Yu. P. Features of synthesis and simulation hierarchically-organized DSS based on fuzzy logic / Yu. P. Kondratenko, Ie. V. Sidenko // Journal of Kherson National Technical University. – 2011. – № 2(41). – С. 150 – 158 [in Ukrainian].
  4. Orlov, А. I. Applied statistics / А. I.Orlov. – Мoscow : Exam, 2007. – 656 p. [in Russian].
  5. Piegat, А.Fuzzy Modelling and Control / А. Piegat ; trans. fromeng. ­­– Мoscow : BINOM, 2012. – 798 p.[in Russian].
  6. Rotshtein А.P. Intellectual technologies of identification: fuzzy logic, genetic algorithms, neural networks / А. P.Rotshtein– Vinnitsa: UNIVERSUM, 1999.– 320 p.[in Russian].
  7. Kondratenko, Y. P. Correction of the Knowledge Database of Fuzzy Decision Support System with Variable Structure of the Input Data : Proceedings of the International Conference Modeling and Simulation /Y. P. Kondratenko, E. V. Sidenko, A. M. Gil-Lafuente (Eds.), V. V. Krasnoproshin (Eds.). – Minsk : Republic of Belarus, 2012. – P. 56–61 [in English].
  8. Kondratenko,Y. P. Decision-Making and Fuzzy Estimation of Quality Level for Cargo Delivery, Proceeding of the 2nd World Conference on Soft Computing / Y. P. Kondratenko, Ie. V. Sidenko. – Baku : Azerbaijan, 2012. – P. 418–423 [in English].
  9. Kondratenko, Y. P. Method of Actual Correction of the Knowledge Database of Fuzzy Decision Support System with Flexible Hierarchical Structure / Y.P. Kondratenko, Ie.V. Sidenko // Journal of Computational Optimization in Economics and Finance. – 2012. – № 2(4). – P. 57–76[in English].
  10. Lin, C. I. Reinforcement learning for an ART-based fuzzy adaptive learning control network / C. I. Lin, C. T. Lin // IEEE Transactions on Neural Networks. – 1996. – № 7(7). – P. 709–731 [in English].
  11. . Bossley, K. M. Neurofuzzy model construction for the modelling of non-linear processes : Proceedings of the 3rd European Control Conference / K. M. Bossley, M. Brown, C. J. Harris. – Rome, Italy, 1995. – P. 2438–2433 [in English].
  12. . Babuska,R.Simplification of fuzzy rule bases : Proceedings of the International Conference EUFIT / R. Babuska, M. Setnes, U. Kaymak, H. R. Von Nauta Lemke. – Aachen, Germany, 1996. – P. 1115–1119 [in English].

 

Published:
Last download:
2017-11-16 10:41:46

[ © KarelWintersky ] [ All articles ] [ All authors ]
[ © Odessa National Polytechnic University, 2014. Any use of information from the site is possible only under the condition that the source link! ]
Яндекс.Метрика