METHOD FOR OBTAINING THE PARAMETERS OF MEMBERSHIP FUNCTIONS OF FUZZY SETS BASED ON REAL DATA FOR AUTOMATED INFORMATION PROCESSING SYSTEMS
https://doi.org/10.21822/2073-6185-2019-46-3-79-86
Abstract
Objectives Development of a method for selecting the type of accessory function and obtaining its parameters to allow subjective personal influences in automated information processing to be excluded.
Method. Existing methods for constructing membership functions were analysed. The research was based on the methods of fuzzy logic and data analysis.
Results. A method for obtaining the parameters of membership functions of fuzzy sets using real data is suggested. It is proposed to use the data obtained from the object under study to determine the kernel of the fuzzy number, as well as derive theoretical information about the object for the carrier. Triangular, trapezoidal, bell-shaped and Gaussian membership functions are considered. The appearance of the membership function can be defined using the criterion of the relations of the kernel to the carrier of a fuzzy set. The results of calculations for obtaining the membership functions based on data on the power consumption of electric motors of different types are given.
Conclusion. The developed method can be used both in decision support systems as well as in automated systems for controlling technological processes. If necessary, the values of the criterion proposed in the article can be revised to take the values included in the set of measured real data into account or to simplify the procedure of automated processing. Further research will use the described method to obtain the terms of linguistic variables.
About the Authors
E. E. BisyanovUkraine
Dr. Sci. (Economy), Cand. Sci. (Technical), Prof., Prof., Department of Specialized Computer Systems
16 Lenin Ave., LNR, Alchevsk 94204
A. A. Gutnik
Ukraine
Graduate Student Department of Specialized Computer Systems
16 Lenin Ave., LNR, Alchevsk 94204
References
1. Levitskiy S.I. Modeli upravleniya proektami v nestabil'noy ekonomicheskoy srede : monografiya / S. I. Levitskiy, Yu. G. Lysenko, A. V. Filippov i dr.; pod red. chl.-kor. NAN Ukrainy, d-ra ekon. nauk, prof. Yu. G. Lysenko. — 2-e izd., pererab. i dop. — Donetsk : Yugo-Vostok, 2009. 354 s. [Levickii S.I. Project management models in an unstable economic environment: monograph / S.I. Levickii, Y.G. Lisenko, A.V. Filippov and others; under the editorship of Corresponding Member of NAS of Ukraine, Dr. Sci. Econ., Professor Y.G. Lisenko. 2nd edition, revised and enlarged. Donetsk : Southeast, 2009. 354 p. (in Russ)]
2. Pegat A. Nechetkoe modelirovanie i upravlenie / A. Pegat; per. s angl. 3-e izd. — M. : BINOM. Laboratoriya znaniy, 2015. — 801 s. [Piegat A. Fuzzy modeling and control / A. Piegat; translation from the English language. — 3rd edition — M.: Binom-press. Knowledge lab, 2015. 801 p. (in Russ)]
3. Nechetkiye mnozhestva v modelyakh upravleniya i iskusstvennogo intellekta/ Pod red. D. A. Pospelova. M.: Nauka. Gl. red. fiz.-mat. lit., 1986. 312 s. (Problemy iskusstvennogo intellekta). [Fuzzy sets in control and artificial intelligence models / Ed. D.A. Pospelova. M .: Science. Ch. ed. Phys.-Math. lit., 1986. 312 p. (Problems of artificial intelligence) (in Russ)]
4. Bashveev Yu.A., Sal'nikov I.I. Funktsiya prinadlezhnosti v sisteme podderzhki prinyatiya resheniya po vyboru mikrokontrollera // XXI vek: itogi proshlogo i problemy nastoyashchego plyus. 2016. №3 (31). S. 89-100 [Bashveev Y.A., Salnikov I.I. The membership functions of decision support system software choosing a microcontroller // XXI century: resumes of the past and challenges of the present plus. 2016. No. 3 (31). pp. 89-100 (in Russ)]
5. Orlov A.I. Teoriya prinyatiya resheniy. Uchebnoe posobie / A.I.Orlov. M.: Izdatel'stvo «Ekzamen», 2005. 656 s. [Orlov A.I. Decision theory. Study guide / A.I. Orlov. M.: Publishing «Exam», 2005. 656 p. (in Russ)]
6. E. Bas, U. Yoclu, E. Egrioglu, Cagdas Hakan Aladag A Fuzzy Time Series Forecasting Method Base on Operation of Union and Feed Forward Artificial Neuron Network // American Journal of Intelligent Systems. — 2015. Vol. 5(3). рр. 81-91
7. Nechetkie mnozhestva i teoriya vozmozhnostey. Poslednie dostizheniya / Per. s angl. / Pod red. R.R. Yagera. M.: Radio i svyaz', 1986. – 408 s. [Fuzzy set and possibility theory. Recent Development / Edited by R.R.Yager. M.: Radio and communication, 1986. 408 p. (in Russ)]
8. Chameau J.L., Santamarina J.C., Membership function I: Comparing methods of Measurement // International Journal of Approximate Reasoning. 1987. Vol. 1. рр.287-301
9. Orlov A.I. Ekspertnye otsenki. // Zhurnal «Zavodskaya laboratoriya». 1996. T.62. № 1. S.54-60. [Orlov A.I. Theory of expert estimates in our country // Industrial Laboratory. 1996. Vol. 62. No. 1. pp. 54-60 (in Russ)]
10. Berestov V.L. Statistika: Uchebnoe posobie. / V.L. Berestov, E.P. Zhilenkova, S.G. Kuznetsov Bryansk: Bryan.gos.inzh.-tekhn.akad., 2014. – 244 s. [Berestov V.L. Statistics: Study guide / V.L. Berestov, E.P. Zhilenkova, S.G. Kuznecov — Bryansk: BSTAEA, 2014. – 244 p. (in Russ)]
11. Low-voltage electric motors for industrial use [Electronic resource] - Available at:: http://www.comsol.ru/katalog/elektrodvigateli/abb/kat/nv_dvigateli_promishlennogo_naznacheniya.pdf (accessed 27.09.2019) (in Russ)]
12. Spravochnik po elektricheskim mashinam. V 2 t. T. 2. / Pod obshch. red. I.P. Kopylova, B.K. Klokova. — M.: Energoatomizdat, 1989. 688 s. [Handbook of electric machines. Vol. 2 of 2 / Edited by I.P. Kopilova, B.K. Klokova. M.: Energoatomizdat, 1989. 688 p. (in Russ)]
Review
For citations:
Bisyanov E.E., Gutnik A.A. METHOD FOR OBTAINING THE PARAMETERS OF MEMBERSHIP FUNCTIONS OF FUZZY SETS BASED ON REAL DATA FOR AUTOMATED INFORMATION PROCESSING SYSTEMS. Herald of Dagestan State Technical University. Technical Sciences. 2019;46(3):79-86. (In Russ.) https://doi.org/10.21822/2073-6185-2019-46-3-79-86