Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10254667" target="_blank" >RIV/61989100:27240/23:10254667 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/23:10254667

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/abs/pii/S0960077923002783" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0960077923002783</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.chaos.2023.113377" target="_blank" >10.1016/j.chaos.2023.113377</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods

Popis výsledku v původním jazyce

One of the key tasks in the economy is forecasting the economic agents&apos; expectations of the future values of economic variables using mathematical models. The behavior of mathematical models can be irregular, including chaotic, which reduces their predictive power. In this paper, we study the regimes of behavior of two economic models and identify irregular dynamics in them. Using these models as an example, we demonstrate the effectiveness of evolutionary algorithms and the continuous deep Q-learning method in combination with Pyragas control method for deriving a control action that stabilizes unstable periodic trajectories and suppresses chaotic dynamics. We compare qualitative and quantitative characteristics of the model&apos;s dynamics before and after applying control and verify the obtained results by numerical simulation. Proposed approach can improve the reliability of forecasting and tuning of the economic mechanism to achieve maximum decision-making efficiency.

Název v anglickém jazyce

Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods

Popis výsledku anglicky

One of the key tasks in the economy is forecasting the economic agents&apos; expectations of the future values of economic variables using mathematical models. The behavior of mathematical models can be irregular, including chaotic, which reduces their predictive power. In this paper, we study the regimes of behavior of two economic models and identify irregular dynamics in them. Using these models as an example, we demonstrate the effectiveness of evolutionary algorithms and the continuous deep Q-learning method in combination with Pyragas control method for deriving a control action that stabilizes unstable periodic trajectories and suppresses chaotic dynamics. We compare qualitative and quantitative characteristics of the model&apos;s dynamics before and after applying control and verify the obtained results by numerical simulation. Proposed approach can improve the reliability of forecasting and tuning of the economic mechanism to achieve maximum decision-making efficiency.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Chaos, Solitons &amp; Fractals

ISSN

0960-0779

e-ISSN

1873-2887

Svazek periodika

170

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

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Kód UT WoS článku

001030254100001

EID výsledku v databázi Scopus

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