Geodesic
Modular model for time series forecasting based on neuro-fuzzy nets and cognitive modelling
Nečetkie sistemy i mâgkie vyčisleniâ, Tome 12 (2017) no. 2, pp. 159-168.

Voir la notice de l'article provenant de la source Math-Net.Ru

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. 
@article{FSSC_2017_12_2_a6,
     author = {S. A. Yarushev and A. N. Averkin and A. V. Fedotova},
     title = {Modular model for time series forecasting based on neuro-fuzzy nets and cognitive modelling},
     journal = {Ne\v{c}etkie sistemy i m\^agkie vy\v{c}isleni\^a},
     pages = {159--168},
     publisher = {mathdoc},
     volume = {12},
     number = {2},
     year = {2017},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/FSSC_2017_12_2_a6/}
}
TY  - JOUR
AU  - S. A. Yarushev
AU  - A. N. Averkin
AU  - A. V. Fedotova
TI  - Modular model for time series forecasting based on neuro-fuzzy nets and cognitive modelling
JO  - Nečetkie sistemy i mâgkie vyčisleniâ
PY  - 2017
SP  - 159
EP  - 168
VL  - 12
IS  - 2
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/FSSC_2017_12_2_a6/
LA  - ru
ID  - FSSC_2017_12_2_a6
ER  - 
%0 Journal Article
%A S. A. Yarushev
%A A. N. Averkin
%A A. V. Fedotova
%T Modular model for time series forecasting based on neuro-fuzzy nets and cognitive modelling
%J Nečetkie sistemy i mâgkie vyčisleniâ
%D 2017
%P 159-168
%V 12
%N 2
%I mathdoc
%U http://geodesic.mathdoc.fr/item/FSSC_2017_12_2_a6/
%G ru
%F FSSC_2017_12_2_a6
S. A. Yarushev; A. N. Averkin; A. V. Fedotova. Modular model for time series forecasting based on neuro-fuzzy nets and cognitive modelling. Nečetkie sistemy i mâgkie vyčisleniâ, Tome 12 (2017) no. 2, pp. 159-168. http://geodesic.mathdoc.fr/item/FSSC_2017_12_2_a6/

[1] Armstrong J. S., “Research needs in forecasting”, International Journal of Forecasting, 1988, no. 4, 449-465 | DOI

[2] Lefevr V. A., “Initial ideas of the logic of reflexive games”, Proceedings of the Conference «Problems of Researching Systems and Structures», AN SSSR Publ., Moscow, 1965 (in Russian)

[3] Soros G., The alchemy of finance, John Wiley Sons, 2003

[4] Averkin A. N., Yarushev S., “Hybrid approach for time series forecasting based on ANFIS and Fuzzy Cognitive Maps”, 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM) (St. Petersburg, Russia, 2017), 379-381 | DOI

[5] Bellman R., Zade L., “Decision-making under vague conditions”, Analysis Questions and Decision-making Procedures, Mir Publ., Moscow, 1976, 172-215 (in Russian) | MR

[6] Rotshtein A. P., Shtovba S. D., Fuzzy Reliability of Algorithmic Processes, Kontinent-Prim Publ., Vinnitsa, 1997, 142 pp. (in Russian)

[7] Averkin A. N., Batyrshin I. Z., Blishun A. F., Silov V. B., Tarasov V. B., Fuzzy Sets in Models of Control and Artificial Intelligence, ed. D. A. Pospelov, Nauka Publ., Moscow, 1986, 312 pp. (in Russian)

[8] Kosko B., “Fuzzy cognitive maps”, International journal of man-machine studies, 24 (1986), 65-75 | DOI | Zbl