An intelligent digital twinning approach for complex circuits

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F24%3A43971891" target="_blank" >RIV/49777513:23220/24:43971891 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1568494624001017?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1568494624001017?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.asoc.2024.111327" target="_blank" >10.1016/j.asoc.2024.111327</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An intelligent digital twinning approach for complex circuits

Popis výsledku v původním jazyce

The digital twinning process is essential for transferring real-world objects to the Metaverse by creating accurate digital versions, known as digital twins. However, complex systems pose challenges in this process. With the increasing utilization of microwave components and circuits in telecommunication systems such as IoT, 5 G, and 6 G, the need for digital twins of these components arises. Nevertheless, high-frequency components exhibit intricate behavior, requiring advanced modeling techniques. Artificial intelligence (AI) provides a powerful tool for enhancing the reliability and accuracy of estimated models in such cases. In this study, a microstrip lowpass filter (LPF) is designed, fabricated, and measured as the physical twin. An intelligent digital twinning approach is employed using a machine learning method based on an adaptive neuro-fuzzy inference system (ANFIS), trained by a subtractive clustering algorithm. The resulting digital twin of the LPF proves valuable for communication networks and IoT applications. Moreover, this research showcases the applicability and accessibility of machine learning in creating digital twins of electromagnetic components for communication cyber-physical systems (CPSs) and the Metaverse. Furthermore, the proposed method exhibits adaptability to various passive and active electrical or electronic circuits. By harnessing the potential of AI and digital twinning, this study presents a robust and accurate approach for modeling and analyzing complex circuits, specifically in the context of communication systems and their integration into the Metaverse. The findings highlight the advantages of an intelligent digital twinning approach and its potential for advancing various domains involving complex circuitry.

Název v anglickém jazyce

An intelligent digital twinning approach for complex circuits

Popis výsledku anglicky

The digital twinning process is essential for transferring real-world objects to the Metaverse by creating accurate digital versions, known as digital twins. However, complex systems pose challenges in this process. With the increasing utilization of microwave components and circuits in telecommunication systems such as IoT, 5 G, and 6 G, the need for digital twins of these components arises. Nevertheless, high-frequency components exhibit intricate behavior, requiring advanced modeling techniques. Artificial intelligence (AI) provides a powerful tool for enhancing the reliability and accuracy of estimated models in such cases. In this study, a microstrip lowpass filter (LPF) is designed, fabricated, and measured as the physical twin. An intelligent digital twinning approach is employed using a machine learning method based on an adaptive neuro-fuzzy inference system (ANFIS), trained by a subtractive clustering algorithm. The resulting digital twin of the LPF proves valuable for communication networks and IoT applications. Moreover, this research showcases the applicability and accessibility of machine learning in creating digital twins of electromagnetic components for communication cyber-physical systems (CPSs) and the Metaverse. Furthermore, the proposed method exhibits adaptability to various passive and active electrical or electronic circuits. By harnessing the potential of AI and digital twinning, this study presents a robust and accurate approach for modeling and analyzing complex circuits, specifically in the context of communication systems and their integration into the Metaverse. The findings highlight the advantages of an intelligent digital twinning approach and its potential for advancing various domains involving complex circuitry.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/EF18_069%2F0009855" target="_blank" >EF18_069/0009855: Elektrotechnické technologie s vysokým podílem vestavěné inteligence</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Applied Soft Computing

ISSN

1568-4946

e-ISSN

1872-9681

Svazek periodika

154

Číslo periodika v rámci svazku

March 2024

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

001185518700001

EID výsledku v databázi Scopus

2-s2.0-85185557979