Usage of selected swarm intelligence algorithms for piecewise linearization

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

Usage of selected swarm intelligence algorithms for piecewise linearization

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10102 - Applied mathematics

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

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

Name of the periodical

Mathematics

ISSN

2227-7390

e-ISSN

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Volume of the periodical

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Issue of the periodical within the volume

5

Country of publishing house

CH - SWITZERLAND

Number of pages

24

Pages from-to

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UT code for WoS article

000771503500001

EID of the result in the Scopus database

2-s2.0-85126336061