Unconventional modelling of complex system via cellular automata and differential evolution

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F15%3AA1601FG2" target="_blank" >RIV/61988987:17310/15:A1601FG2 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Unconventional modelling of complex system via cellular automata and differential evolution

Popis výsledku v původním jazyce

The article deals with principles of cellular automata(CA) and differential evolution(DE) within simulation of an epidemic process. CA consist of many identical components, each simple, but together capable of complex behaviour. The proposed CA supportsto find rules of the transition function that represents the model of a studied epidemic. Search for models a studied epidemic belongs to inverse problems whose solution lies in a finding of local rules guaranteeing a desired global behaviour. The epidemic models have the control parameters and their setting significantly influences the behaviour of the models. One way how to get proper values of the control parameters is use DE. Simulations of illness were performed using both described approaches. Theaim of the paper is to show a course of simulations for different rules of the transition function and how to find a suitable model of a studied epidemic in the case of inverse problems using a sufficient amount of local rules of a trans

Název v anglickém jazyce

Unconventional modelling of complex system via cellular automata and differential evolution

Popis výsledku anglicky

The article deals with principles of cellular automata(CA) and differential evolution(DE) within simulation of an epidemic process. CA consist of many identical components, each simple, but together capable of complex behaviour. The proposed CA supportsto find rules of the transition function that represents the model of a studied epidemic. Search for models a studied epidemic belongs to inverse problems whose solution lies in a finding of local rules guaranteeing a desired global behaviour. The epidemic models have the control parameters and their setting significantly influences the behaviour of the models. One way how to get proper values of the control parameters is use DE. Simulations of illness were performed using both described approaches. Theaim of the paper is to show a course of simulations for different rules of the transition function and how to find a suitable model of a studied epidemic in the case of inverse problems using a sufficient amount of local rules of a trans

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Swarm and Evolutionary Computation

ISSN

2210-6502

e-ISSN

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Svazek periodika

25

Číslo periodika v rámci svazku

SI: RAMONA

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

52-62

Kód UT WoS článku

000367860600006

EID výsledku v databázi Scopus

2-s2.0-84952630886