Dependency of GPA-ES Algorithm Efficiency on ES Parameters Optimization Strength

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F19%3A39914633" target="_blank" >RIV/00216275:25530/19:39914633 - isvavai.cz</a>

Result on the web

<a href="http://jaec.vn/index.php/JAEC/article/view/226/99" target="_blank" >http://jaec.vn/index.php/JAEC/article/view/226/99</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.25073/jaec.201931.226" target="_blank" >10.25073/jaec.201931.226</a>

Result language

angličtina

Original language name

Dependency of GPA-ES Algorithm Efficiency on ES Parameters Optimization Strength

Original language description

In herein presented work, the relation between number of ES iterations and convergence of the whole GPA-ES hybrid algorithm will be studied due to increasing needs to analyze and model large data sets. Evolutionary algorithms are applicable in the areas which are not covered by other artificial intelligence or soft computing techniques like neural networks and deep learning like search of algebraic model of data. The difference between time and algorithmic complexity will be also mentioned as well as the problems of multitasking implementation of GPA, where external influences complicate increasing of GPA efficiency via Pseudo Random Number Generator (PRNG) choice optimization. Hybrid evolutionary algorithms like GPA-ES uses GPA for solution structure development and Evolutionary Strategy (ES) for parameters identification are controlled by many parameters. The most significant are sizes of GPA population and sizes of ES populations related to each particular individual in GPA population. There is also limit of ES algorithm evolutionary cycles. This limit plays two contradictory roles. On one side bigger number of ES iterations means less chance to omit good solution for wrongly identified parameters, on the opposite side large number of ES iterations significantly increases computational time and thus limits application domain of GPA-ES algorithm.

Czech name

—

Czech description

—

Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF17_049%2F0008394" target="_blank" >EF17_049/0008394: Cooperation in Applied Research between the University of Pardubice and companies, in the Field of Positioning, Detection and Simulation Technology for Transport Systems (PosiTrans)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

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

Name of the periodical

Journal of Advanced Engineering and Computation

ISSN

1859-2244

e-ISSN

—

Volume of the periodical

3

Issue of the periodical within the volume

1

Country of publishing house

VN - VIET NAM

Number of pages

8

Pages from-to

304-311

UT code for WoS article

—

EID of the result in the Scopus database

—