prikaz prve stranice dokumenta Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash
  Preuzmi
PDF 5.15 MB
Znanstveni rad - Izvorni znanstveni rad
Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash
Mathematics, 12 (2024), 1; 1-25. https://doi.org/10.3390/math12010066
Kovačević, Miljan; Hadzima-Nyarko, Marijana; Netinger Grubeša, Ivanka; Radu, Dorin; Lozančić, Silva

Citirajte ovaj rad

Kovačević, M., Hadzima Nyarko, M., Netinger Grubeša, I., Radu, D. i Lozančić, S. (2024). Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash. Mathematics, 12. (1), 1-25. doi: 10.3390/math12010066

Kovačević, Miljan, et al. "Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash." Mathematics, vol. 12, br. 1, 2024, str. 1-25. https://doi.org/10.3390/math12010066

Kovačević, Miljan, Marijana Hadzima Nyarko, Ivanka Netinger Grubeša, Dorin Radu i Silva Lozančić. "Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash." Mathematics 12, br. 1 (2024): 1-25. https://doi.org/10.3390/math12010066

Kovačević, M., et al. (2024) 'Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash', Mathematics, 12(1), str. 1-25. doi: 10.3390/math12010066

Kovačević M, Hadzima Nyarko M, Netinger Grubeša I, Radu D, Lozančić S. Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash. Mathematics [Internet]. 2024. [pristupljeno 21.02.2025.];12(1):1-25. doi: 10.3390/math12010066

M. Kovačević, M. Hadzima Nyarko, I. Netinger Grubeša, D. Radu i S. Lozančić, "Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash", Mathematics, vol. 12, br. 1, str. 1-25, 2024. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:133:894439. [Citirano: 21.02.2025.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:133:894439
Prijavite se u repozitorij kako biste mogli spremiti objekt u svoju listu.
Podaci o radu
Naslov (engleski)Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Green Concretes with Rice Husk Ash
AutorMiljan Kovačević
AutorMarijana Hadzima-Nyarko
AutorIvanka Netinger Grubeša
AutorDorin Radu
AutorSilva Lozančić
Autorova ustanovaSveučilište Josipa Jurja Strossmayera u Osijeku
Građevinski i arhitektonski fakultet Osijek
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Građevinarstvo
Sažetak (engleski)
To promote sustainable growth and minimize the greenhouse effect, rice husk fly ash can be used instead of a certain amount of cement. The research models the effects of using rice fly ash as a substitute for regular Portland cement on the compressive strength of concrete. In this study, different machine-learning techniques are investigated and a procedure to determine the optimal model is provided. A database of 909 analyzed samples forms the basis for creating forecast models. The derived models are assessed using the accuracy criteria RMSE, MAE, MAPE, and R. The research shows that artificial intelligence techniques can be used to model the compressive strength of concrete with acceptable accuracy. It is also possible to evaluate the importance of specific input variables and their influence on the strength of such concrete.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - domaća recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaMathematics
Brojčani podacivol. 12, br. 1, str. 1-25
e-ISSN2227-7390
DOIhttps://doi.org/10.3390/math12010066
URN:NBNurn:nbn:hr:133:894439
Datum objave publikacije2024
URL dokumentahttps://www.mdpi.com/2227-7390/12/1/66
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje-Dijeli pod istim uvjetima 3.0 (CC BY-SA 3.0)
Datum i vrijeme pohrane2025-02-03 12:59:29