Romanov Vadim Nikolaevich
G. V. Plekhanov Saint Petersburg State Mining Institute and Technical University
Abstract. The paper investigates fuzzy models use in classification problems on the basis of data representation in the form of fuzzy gradations proposed by the author. The comparison of various measures of objects matching with classes and their influence on classification results is carried out. The author shows the advantages of the proposed approach, which enables to extend the range of solvable problems, improve the reliability of objects distribution in classes, reduce the complexity of calculations.
Key words and phrases: классификация, диагностирование, нечеткие модели, множество эталонов, степень согласования, мера расстояния, classification, diagnosing, fuzzy models, variety of standards, degree of matching, measure of distance
Open the whole article in PDF format. Free PDF-files viewer can be downloaded .
References:
Aivazyan S. A., Bukhshtaber V. M., Enyukov I. S., Meshalkin L. D. Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti. M.: Finansy i statistika, 1989. 607 s.
Nechetkie mnozhestva i teoriya vozmozhnostei / pod red. R. Yagera. M.: Radio i svyaz', 1986. 408 s.
Romanov V. N. Klasternyi analiz na osnove nechetkikh modelei // Al'manakh sovremennoi nauki i obrazovaniya. Tambov: Gramota, 2013. № 10 (77). S. 147-151.
Romanov V. N. Nechetkie modeli v teorii sistem. SPb.: LEMA, 2014. 123 s.
Romanov V. N. Nechetkie modeli prinyatiya reshenii // Al'manakh sovremennoi nauki i obrazovaniya. Tambov: Gramota, 2013. № 5 (72). S. 144-147.
Romanov V. N. Nechetkie sistemy. SPb.: LEMA, 2009. 183 s.
Русский
