Title :
A hybrid grey-fuzzy-neural networks model for enterprises´ bankruptcy
Author :
Scarlat, Emil ; Delcea, Camelia
Author_Institution :
Dept. of Cybern., Univ. of Econ., Bucharest, Romania
Abstract :
This paper attempts to put forward a hybrid model which combines the advantages offered by grey systems theory, fuzzy theory and neural networks. While φ -fuzzy sub-set offers the suitable tools for the treatment of uncertainty and subjectivity, grey systems theory is used for variables selection. Also, neural networks pattern recognition facility is used in order to determine each company´s bankruptcy stage through its interconnection with the other companies that are conducting their business in the same field. Compared with a simple model of pattern recognition, our model succeeded in getting a higher accuracy rate. A numerical example is presented in order to better understand the proposed model.
Keywords :
corporate modelling; fuzzy neural nets; fuzzy set theory; grey systems; pattern recognition; φ -fuzzy subset; enterprise bankruptcy; fuzzy set theory; grey systems theory; hybrid grey-fuzzy-neural network model; neural network pattern recognition facility; variable selection; Artificial neural networks; Geology; Technological innovation;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596526