Publication detail

Application of Neuro-Fuzzy Approach in Predicting the Number of Bankruptcies of Legal Persons in the Czech Republic

ŠEBESTOVÁ, M.

Original Title

Application of Neuro-Fuzzy Approach in Predicting the Number of Bankruptcies of Legal Persons in the Czech Republic

Type

conference paper

Language

English

Original Abstract

This article deals with the application of the neuro-fuzzy approach in estimating the number of companies going bankrupt in the Czech Republic. The prediction is based on macroeconomic indicators from 2011–2016, namely inflation, interest rate and unemployment rate. Unlike statistical models, the neuro-fuzzy models have the advantage of rules made up directly from the used data, and therefore they enable modelling of complex, dynamic and non-linear problems. Based on the obtained results, it can be stated that the designed ANFIS (Adaptive Neuro-Fuzzy Inference System) is able to predict the number of financial failures of companies with sufficient accuracy and thus give a picture of the future market development.

Keywords

Neuro-fuzzy, bankruptcy, macroeconomic indicators

Authors

ŠEBESTOVÁ, M.

Released

8. 11. 2017

Publisher

International Business Information Management Association (IBIMA)

Location

Madrid, Spain

ISBN

978-0-9860419-9-0

Book

Vision 2020: Sustainable Economic development, Innovation Management, and Global Growth

Edition number

30

Pages from

1166

Pages to

1174

Pages count

8

BibTex

@inproceedings{BUT141996,
  author="Monika {Šebestová}",
  title="Application of Neuro-Fuzzy Approach in Predicting the Number of Bankruptcies of Legal Persons in
the Czech Republic",
  booktitle="Vision 2020: Sustainable Economic development, Innovation Management, and Global Growth",
  year="2017",
  number="30",
  pages="1166--1174",
  publisher="International Business Information Management Association (IBIMA)",
  address="Madrid, Spain",
  isbn="978-0-9860419-9-0"
}