Usage of selected swarm intelligence algorithms for piecewise linearization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F22%3AA2302DJK" target="_blank" >RIV/61988987:17310/22:A2302DJK - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2227-7390/10/5/808#cite" target="_blank" >https://www.mdpi.com/2227-7390/10/5/808#cite</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/math10050808" target="_blank" >10.3390/math10050808</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Usage of selected swarm intelligence algorithms for piecewise linearization

Popis výsledku v původním jazyce

The paper introduces a new approach to enhance optimization algorithms when solving the piecewise linearization problem of a given function. Eight swarm intelligence algorithms were selected to be experimentally compared. The problem is represented by the calculation of the distance between the original function and the estimation from the piecewise linear function. Here, the piecewise linearization of 2D functions is studied. Each of the employed swarm intelligence algorithms is enhanced by a newly proposed automatic detection of the number of piecewise linear parts that determine the discretization points to calculate the distance between the original and piecewise linear function. The original algorithms and their enhanced variants are compared on several examples of piecewise linearization problems. The results show that the enhanced approach performs sufficiently better when it creates a very promising approximation of functions. On the second thought, the degree of precision is slightly decreased by the focus on the speed of the optimization process.

Název v anglickém jazyce

Usage of selected swarm intelligence algorithms for piecewise linearization

Popis výsledku anglicky

The paper introduces a new approach to enhance optimization algorithms when solving the piecewise linearization problem of a given function. Eight swarm intelligence algorithms were selected to be experimentally compared. The problem is represented by the calculation of the distance between the original function and the estimation from the piecewise linear function. Here, the piecewise linearization of 2D functions is studied. Each of the employed swarm intelligence algorithms is enhanced by a newly proposed automatic detection of the number of piecewise linear parts that determine the discretization points to calculate the distance between the original and piecewise linear function. The original algorithms and their enhanced variants are compared on several examples of piecewise linearization problems. The results show that the enhanced approach performs sufficiently better when it creates a very promising approximation of functions. On the second thought, the degree of precision is slightly decreased by the focus on the speed of the optimization process.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Mathematics

ISSN

2227-7390

e-ISSN

—

Svazek periodika

—

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

24

Strana od-do

—

Kód UT WoS článku

000771503500001

EID výsledku v databázi Scopus

2-s2.0-85126336061