Soft computing methods for estimating the uniaxial compressive strength of intact rock from index tests

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68145535%3A_____%2F15%3A00450214" target="_blank" >RIV/68145535:_____/15:00450214 - isvavai.cz</a>

Výsledek na webu

<a href="http://ac.els-cdn.com/S1365160915300708/1-s2.0-S1365160915300708-main.pdf?_tid=318a7cec-8929-11e5-a3b8-00000aacb35f&acdnat=1447324752_2a9d947b573773f88da353a16f850eac" target="_blank" >http://ac.els-cdn.com/S1365160915300708/1-s2.0-S1365160915300708-main.pdf?_tid=318a7cec-8929-11e5-a3b8-00000aacb35f&acdnat=1447324752_2a9d947b573773f88da353a16f850eac</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ijrmms.2015.10.012" target="_blank" >10.1016/j.ijrmms.2015.10.012</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Soft computing methods for estimating the uniaxial compressive strength of intact rock from index tests

Popis výsledku v původním jazyce

Uniaxial compressive strength ( UCS ) is one of the most widely used rock mechanical parameters in rock engineering. Determi- nation of this parameter in the laboratory, however, requires quality rock specimens. The use of various index tests that require little or no specimen preparation and are easier to perform as well as less expensive than the uniaxial compression test has always been attractive in order to predict UCS of rock materials empirically 1 ? 16 . Amongst different predictive models suchas re- gression analyses, fuzzy inference system and neural network approaches ; regression analyses are commonly employed to es- tablish a predictive model to estimate UCS 17 . In the last decade or so, however, the use of soft computing methods (e.g. fuzzy in- ference system (FIS), arti fi cial neural network (ANN) and adaptive neuro ? fuzzy inference system (ANFIS)) in order to establish pre- dictive models has also gained signi fi cant attention in the areas of rock mechanics and eng

Název v anglickém jazyce

Soft computing methods for estimating the uniaxial compressive strength of intact rock from index tests

Popis výsledku anglicky

Uniaxial compressive strength ( UCS ) is one of the most widely used rock mechanical parameters in rock engineering. Determi- nation of this parameter in the laboratory, however, requires quality rock specimens. The use of various index tests that require little or no specimen preparation and are easier to perform as well as less expensive than the uniaxial compression test has always been attractive in order to predict UCS of rock materials empirically 1 ? 16 . Amongst different predictive models suchas re- gression analyses, fuzzy inference system and neural network approaches ; regression analyses are commonly employed to es- tablish a predictive model to estimate UCS 17 . In the last decade or so, however, the use of soft computing methods (e.g. fuzzy in- ference system (FIS), arti fi cial neural network (ANN) and adaptive neuro ? fuzzy inference system (ANFIS)) in order to establish pre- dictive models has also gained signi fi cant attention in the areas of rock mechanics and eng

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DH - Báňský průmysl včetně těžby a zpracování uhlí

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

International Journal of Rock Mechanics and Mining Sciences

ISSN

1365-1609

e-ISSN

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Svazek periodika

80

Číslo periodika v rámci svazku

December 2015

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

7

Strana od-do

418-424

Kód UT WoS článku

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EID výsledku v databázi Scopus

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