Prediction of Concrete Strength using Floating Centroids Method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F13%3A86089354" target="_blank" >RIV/61989100:27740/13:86089354 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/SMC.2013.173" target="_blank" >http://dx.doi.org/10.1109/SMC.2013.173</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SMC.2013.173" target="_blank" >10.1109/SMC.2013.173</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction of Concrete Strength using Floating Centroids Method

Popis výsledku v původním jazyce

Concrete is viewed as the most important cementbased composite material in the field of civil engineering. Its strength is considered the most important among its mechanical properties. Although the value of strength can be directly forecasted, the estimation of strength grade remains particularly important because concrete mortar is non-uniform, and practical preparation and curing cannot be fully simulated under laboratory conditions. In this paper, concrete strength grade was predicted by using the floating centroids method neural network classifier, which removes the fixed-centroid constraint and increases the possibility of finding an optimal neural network. Experimental results show that concrete strength prediction performance is improved by employing the floating centroids method.

Název v anglickém jazyce

Prediction of Concrete Strength using Floating Centroids Method

Popis výsledku anglicky

Concrete is viewed as the most important cementbased composite material in the field of civil engineering. Its strength is considered the most important among its mechanical properties. Although the value of strength can be directly forecasted, the estimation of strength grade remains particularly important because concrete mortar is non-uniform, and practical preparation and curing cannot be fully simulated under laboratory conditions. In this paper, concrete strength grade was predicted by using the floating centroids method neural network classifier, which removes the fixed-centroid constraint and increases the possibility of finding an optimal neural network. Experimental results show that concrete strength prediction performance is improved by employing the floating centroids method.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

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

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013

ISBN

978-0-7695-5154-8

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

988-992

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Manchester

Datum konání akce

13. 10. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—