This article is cited in 4 papers

Modular model for time series forecasting based on neuro-fuzzy nets and cognitive modelling

S. A. Yarushev^a, A. N. Averkin^b, A. V. Fedotova<sup>c

a</sup> University "Dubna", Dubna
^b Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow
^c Bauman Moscow State Technical University, Moscow

Abstract: The paper considers the task of constructing a hybrid time-series forecasting system based on fuzzy cognitive maps and neural networks. This approach allows us to take into account both the quantitative and qualitative characteristics of the time series. For completeness, the features of fuzzy cognitive maps and their application in time series prediction problems are given. Also, the developed genetic algorithm for learning fuzzy cognitive maps is presented, which makes it possible to avoid the laborious task of manually adjusting the cognitive map.

Keywords: time series, fuzzy cognitive maps, neural networks, forecasting, time series analysis, fuzzy systems.

UDC: 004.415.2

Received: 04.09.2017
Revised: 16.12.2017

DOI: 10.26456/fssc31