A Support Vector Regression-Based Method for Stone Powder Detection in Machine-Made Sand DOI Open Access

Faken Shi,

Yingying Wang, Lili Pei

et al.

Advances in transdisciplinary engineering, Journal Year: 2024, Volume and Issue: unknown

Published: June 17, 2024

Aiming at the problems of cumbersome steps, low accuracy and difficult to quantify in detection method stone powder content machine-made sand, a quantitative is proposed. Based on image segmentation results, attached sand surface scattered were calculated separately. Then, support vector regression (SVM) model was used obtain mapping relationship between two methylene blue value total sand. The experimental results show that obtained 0.9239 proves there high correlation value, thus verifying effectiveness quantifying powder. for proposed this paper further realises function qualitative analysis, provides new technical quality process also has important practical significance direction construction smart city.

Language: Английский

A Support Vector Regression-Based Method for Stone Powder Detection in Machine-Made Sand DOI Open Access

Faken Shi,

Yingying Wang, Lili Pei

et al.

Advances in transdisciplinary engineering, Journal Year: 2024, Volume and Issue: unknown

Published: June 17, 2024

Aiming at the problems of cumbersome steps, low accuracy and difficult to quantify in detection method stone powder content machine-made sand, a quantitative is proposed. Based on image segmentation results, attached sand surface scattered were calculated separately. Then, support vector regression (SVM) model was used obtain mapping relationship between two methylene blue value total sand. The experimental results show that obtained 0.9239 proves there high correlation value, thus verifying effectiveness quantifying powder. for proposed this paper further realises function qualitative analysis, provides new technical quality process also has important practical significance direction construction smart city.

Language: Английский

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