2023
DOI: 10.3390/app13074116
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Application of Data Mining Techniques to Predict Luminance of Pavement Aggregate

Abstract: The primary purpose of the analysis presented here is to assess the feasibility of effectively predicting the aggregate luminance coefficient. Current road lighting standards and recommendations are based on assessing the level and distribution of luminance on the road surface. The brightness of a road surface depends on the amount of light falling on it, as well as the reflective properties of the road surface, which in turn depend on its physical condition, type and mineralogical composition. The complexity … Show more

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Cited by 1 publication
(9 citation statements)
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“…Despite advanced luminance ratio measurement methods, there are insufficient analyses of the extent of aggregate luminance ratio estimation in the world literature. The conclusions of the study, as reported in [15], indicate that the mineralogical composition of the aggregate is an important aspect in assessing the luminance level of the aggregate. The promising results have encouraged further work to evaluate the luminance coefficient of the mineral mix.…”
Section: Introductionmentioning
confidence: 81%
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“…Despite advanced luminance ratio measurement methods, there are insufficient analyses of the extent of aggregate luminance ratio estimation in the world literature. The conclusions of the study, as reported in [15], indicate that the mineralogical composition of the aggregate is an important aspect in assessing the luminance level of the aggregate. The promising results have encouraged further work to evaluate the luminance coefficient of the mineral mix.…”
Section: Introductionmentioning
confidence: 81%
“…The detailed process of applying the boosted random tree (BT) algorithm required to predict the luminance ratio Qd is explained in detail in the article [15]. The results that fell within its scope provide the foundation for the search for further links that are the subject of this article.…”
Section: Luminance Coefficient Qd Of the Aggregate Vs Mineralogical C...mentioning
confidence: 99%
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