Prediction of peak particle velocity caused by blasting through the combinations of boosted-chaid and svm models with various kernels

Zeng, Jie and Roussis, Panayiotis C. and Mohammed, Ahmed Salih and Maraveas, Chrysanthos and Fatemi, Seyed Alireza and Armaghani, Danial Jahed and Asteris, Panagiotis G. (2021) Prediction of peak particle velocity caused by blasting through the combinations of boosted-chaid and svm models with various kernels. Applied Sciences, 11 (8). ISSN 2076-3417, DOI https://doi.org/10.3390/app11083705.

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Abstract

This research examines the feasibility of hybridizing boosted Chi-Squared Automatic Interaction Detection (CHAID) with different kernels of support vector machine (SVM) techniques for the prediction of the peak particle velocity (PPV) induced by quarry blasting. To achieve this objective, a boosting-CHAID technique was applied to a big experimental database comprising six input variables. The technique identified four input parameters (distance from blast-face, stemming length, powder factor, and maximum charge per delay) as the most significant parameters affecting the prediction accuracy and utilized them to propose the SVM models with various kernels. The kernel types used in this study include radial basis function, polynomial, sigmoid, and linear. Several criteria, including mean absolute error (MAE), correlation coefficient (R), and gains, were calculated to evaluate the developed models' accuracy and applicability. In addition, a simple ranking system was used to evaluate the models' performance systematically. The performance of the R and MAE index of the radial basis function kernel of SVM in training and testing phases, respectively, confirm the high capability of this SVM kernel in predicting PPV values. This study successfully demonstrates that a combination of boosting-CHAID and SVM models can identify and predict with a high level of accuracy the most effective parameters affecting PPV values.

Item Type: Article
Funders: Science and Technology Research Program of Chongqing Municipal Education Commission [KJQN201804305] [KJQN201904307]
Uncontrolled Keywords: Ground vibration; Blasting operation; Boosting-CHAID; Support vector machine; Input selection
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering > Department of Civil Engineering
Depositing User: Ms Zaharah Ramly
Date Deposited: 17 Jul 2022 06:38
Last Modified: 17 Jul 2022 06:38
URI: http://eprints.um.edu.my/id/eprint/28821

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