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Classification and regression tree technique in estimating peak particle velocity caused by blasting

Khandelwal, M. and Armaghani, D. J. and Faradonbeh, R. S. and Yellishetty, M. and Majid, M. Z. A. and Monjezi, M. (2017) Classification and regression tree technique in estimating peak particle velocity caused by blasting. Engineering with Computers, 33 (1). pp. 45-53. ISSN 0177-0667

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Official URL: http://dx.doi.org/10.1007%2Fs00366-016-0455-0


Blasting is a widely used technique for rock fragmentation in surface mines and tunneling projects. The ground vibrations produced by blasting operations are the main concern for the industries undertaking blasting operations, which can damage the surrounding structures, adjacent rock masses, roads and slopes in the vicinity. Therefore, proper prediction of blast-induced ground vibrations is essential to demarcate the safety area of blasting. In this research, classification and regression tree (CART) as a rule-based method was used to predict the peak particle velocity through a database comprising of 51 datasets with results of maximum charge per delay and distance from the blast face were fixed as model inputs. For comparison, the empirical and multiple regression (MR) models were also applied and proposed for peak particle velocity prediction. Performance of the proposed models were compared and evaluated using three statistical criteria, namely coefficient of correlation (R2), root mean square error (RMSE) and variance account for (VAF). Comparison of the obtained results demonstrated that the CART technique is more reliable for predicting the peak particle velocity than the MR and empirical models and it can be introduced as a new technique in this field.

Item Type:Article
Uncontrolled Keywords:blasting, classification and regression tree technique, peak particle velocity
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Civil Engineering
ID Code:80340
Deposited By: Narimah Nawil
Deposited On:10 May 2019 15:16
Last Modified:10 May 2019 15:16

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