Bayesian networks' development based on noisy-max nodes for modeling investment

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F19%3A43894893" target="_blank" >RIV/44555601:13440/19:43894893 - isvavai.cz</a>

Result on the web

<a href="http://ceur-ws.org/Vol-2386/paper1.pdf" target="_blank" >http://ceur-ws.org/Vol-2386/paper1.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Bayesian networks' development based on noisy-max nodes for modeling investment

Original language description

This article focuses on the use of Bayesian networks for analyzing the growth relationship of Ukraine&apos;s gross domestic product (GDP) from the volume of investment in the transport industry and offers a comparative description of the use of different structural training algorithms. It is shown that Noisy-max nodes as compared to General nodes provide relatively high initial accuracy. General nodes require a repeated validation procedure. When using the Hirerical sampling method, the accuracy of the network result with General nodes remains unchanged, and with Noisy-max nodes, it increases (in our case, by 12.32%). However, Noisy-max nodes entail an increase in time and computational costs.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

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

Article name in the collection

CEUR Workshop Proceedings

ISBN

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ISSN

1613-0073

e-ISSN

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Number of pages

10

Pages from-to

"nestrankovano"

Publisher name

CEUR-WS

Place of publication

Paris

Event location

Shatsk

Event date

Jun 2, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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