prikaz prve stranice dokumenta Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters
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Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters
Lubricants, 12 (2024), 1; 23. https://doi.org/10.3390/lubricants12010023
Ban, Ivana; Deluka-Tibljaš, Aleksandra; Ružić, Igor

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Ban, I., Deluka Tibljaš, A. i Ružić, I. (2024). Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters. Lubricants, 12. (1). doi: 10.3390/lubricants12010023

Ban, Ivana, et al. "Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters." Lubricants, vol. 12, br. 1, 2024. https://doi.org/10.3390/lubricants12010023

Ban, Ivana, Aleksandra Deluka Tibljaš i Igor Ružić. "Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters." Lubricants 12, br. 1 (2024). https://doi.org/10.3390/lubricants12010023

Ban, I., Deluka Tibljaš, A. i Ružić, I. (2024) 'Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters', Lubricants, 12(1). doi: 10.3390/lubricants12010023

Ban I, Deluka Tibljaš A, Ružić I. Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters. Lubricants [Internet]. 12.01.2024. [pristupljeno 03.04.2025.];12(1). doi: 10.3390/lubricants12010023

I. Ban, A. Deluka Tibljaš i I. Ružić, "Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters", Lubricants, vol. 12, br. 1, Siječanj 2024. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:157:077459. [Citirano: 03.04.2025.]

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Podaci o radu
Naslov (engleski)Skid Resistance Performance Assessment by a PLS Regression-Based Predictive Model with Non-Standard Texture Parameters
AutorIvana Ban
AutorAleksandra Deluka-Tibljaš
AutorIgor Ružić
Autorova ustanovaSveučilište u Rijeci
Građevinski fakultet
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Građevinarstvo
Prometnice
Sažetak (engleski)
The importance of skid resistance performance assessment in pavement engineering and management is crucial due to its direct influence on road safety features. This paper provides a new approach to skid resistance predictive model definition based on experimentally obtained texture roughness parameters. The originally developed methodology is based on a photogrammetry technique for pavement surface data acquisition and analysis, named the Close-Range Orthogonal Photogrammetry (CROP) method. Texture roughness features were analyzed on pavement surface profiles extracted from surface 3D models, obtained by the CROP method. Selected non-standard roughness parameters were used as predictors in the skid resistance model. The predictive model was developed by the partial least squares (PLS) method as a feature engineering procedure in the regression analysis framework. The proposed model was compared to the simple linear regression model with a traditional texture parameter Mean Profile Depth as the predictor, showing better predictive strength when multiple non-standard texture parameters were used.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaLubricants
Brojčani podacivol. 12, br. 1, 23
e-ISSN2075-4442
DOIhttps://doi.org/10.3390/lubricants12010023
URN:NBNurn:nbn:hr:157:077459
Datum objave publikacije2024-01-12
ProjektŠifra: uniri-tehnic-18-143 – 1289
Naziv (hrvatski): Prometna infrastruktura u funkciji održive urbane mobilnosti
Naziv (engleski): Transport infrastructure in the function of sustainable mobility
Voditelj: Aleksandra Deluka-Tibljaš
Pravna nadležnost: Hrvatska
Financijer: Sveučilište u Rijeci
URL dokumentahttps://www.mdpi.com/2075-4442/12/1/23
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Datum i vrijeme pohrane2025-03-25 08:49:32