Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F20%3A39916135" target="_blank" >RIV/00216275:25410/20:39916135 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0925231220303489" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0925231220303489</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.neucom.2020.03.013" target="_blank" >10.1016/j.neucom.2020.03.013</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series

Popis výsledku v původním jazyce

In many real-world forecasting problems, the time series under investigation can be approximated. In that case, instead of dealing with its exact values, only their minima and maxima achieved in the predefined periods are considered. Such an approximation forms interval-valued time series (ITS). To forecast ITS, we propose a new method that relies on fuzzy cognitive maps (FCMs). We adapt standard FCMs to the forecasting of ITS using interval-valued intuitionistic fuzzy sets. In this way, we develop a forecasting model called the Intuitionistic Fuzzy Grey Cognitive Map (IFGCM). We validate our IFGCM using publicly available stock market data for 10 indexes for which the estimation of potential investment losses (minima) and gains (maxima) is crucial. The results of these experiments prove the high efficiency of the IFGCM, especially compared with state-of-the-art models.

Název v anglickém jazyce

Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series

Popis výsledku anglicky

In many real-world forecasting problems, the time series under investigation can be approximated. In that case, instead of dealing with its exact values, only their minima and maxima achieved in the predefined periods are considered. Such an approximation forms interval-valued time series (ITS). To forecast ITS, we propose a new method that relies on fuzzy cognitive maps (FCMs). We adapt standard FCMs to the forecasting of ITS using interval-valued intuitionistic fuzzy sets. In this way, we develop a forecasting model called the Intuitionistic Fuzzy Grey Cognitive Map (IFGCM). We validate our IFGCM using publicly available stock market data for 10 indexes for which the estimation of potential investment losses (minima) and gains (maxima) is crucial. The results of these experiments prove the high efficiency of the IFGCM, especially compared with state-of-the-art models.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA19-15498S" target="_blank" >GA19-15498S: Modelování emocí ve verbální a neverbální manažerské komunikaci pro predikci podnikových finančních rizik</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Neurocomputing

ISSN

0925-2312

e-ISSN

—

Svazek periodika

400

Číslo periodika v rámci svazku

August

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

173-185

Kód UT WoS článku

000544724700014

EID výsledku v databázi Scopus

2-s2.0-85081961194