Abstract: The problem of corporations’ bankruptcy risk forecasting under uncertainty is considered in this paper. The application of neo-fuzzy cascade neural networks is suggested. The experimental investigations of cascade neo-fuzzy networks for bankruptcy risk forecasting for Ukrainian corporations were carried out and their efficiency was estimated and compared with fuzzy neural networks with algorithms of Mamdani, Tsukamoto and classical statistical methods.

Keywords: bankruptcy risk forecasting, cascade neo-fuzzy network, fuzzy networks of Mamdani and Tsukamoto

ACM Classification Keywords: I.2 Artificial Intelligence; I.5.1 Models; Neural Nets

Link:

ПРОГНОЗИРОВАНИЕ РИСКА БАНКРОТСТВА КОРПОРАЦИЙ В УСЛОВИЯХ НЕОПРЕДЕЛЕННОСТИ С ИСПОЛЬЗОВАНИЕМ НЕЧЕТКИХ НЕЙРОННЫХ СЕТЕЙ (Bankruptcy risk forecasting under uncertainty with application of fuzzy neural networks)

Ови Нафас Агаи аг Гамиш, Юрий Зайченко

http://www.foibg.com/ijitk/ijitk-vol08/ijitk08-04-p02.pdf