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Development of GP and GEP models to estimate an environmental issue induced by blasting operation

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Abstract

Air overpressure (AOp) is one of the most adverse effects induced by blasting in the surface mines and civil projects. So, proper evaluation and estimation of the AOp is important for minimizing the environmental problems resulting from blasting. The main aim of this study is to estimate AOp produced by blasting operation in Miduk copper mine, Iran, developing two artificial intelligence models, i.e., genetic programming (GP) and gene expression programming (GEP). Then, the accuracy of the GP and GEP models has been compared to multiple linear regression (MLR) and three empirical models. For this purpose, 92 blasting events were investigated, and subsequently, the AOp values were carefully measured. Moreover, in each operation, the values of maximum charge per delay and distance from blast points, as two effective parameters on the AOp, were measured. After predicting by the predictive models, their performance prediction was checked in terms of variance account for (VAF), coefficient of determination (CoD), and root mean square error (RMSE). Finally, it was found that the GEP with VAF of 94.12%, CoD of 0.941, and RMSE of 0.06 is a more precise model than other predictive models for the AOp prediction in the Miduk copper mine, and it can be introduced as a new powerful tool for estimating the AOp resulting from blasting.

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Abbreviations

ANN:

Artificial neural network

AOp:

Air overpressure

CoD:

Coefficient of determination

CPs:

Computer programs

D:

Distance between monitoring station and blast point

EAs:

Evolutionary algorithms

ETs:

Expression trees

F:

Function set

GA:

Genetic algorithm

GEP:

Gene expression programming

GP:

Genetic programming

ICA:

Imperialist competitive algorithm

MC:

Maximum charge used per delay

MLR:

Multiple linear regression

PSO:

Particle swarm optimization

RMSE:

Root mean square error

T:

Terminal set

USBM:

US Bureau of Mines

VAF:

Variance account for

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Correspondence to Mahdi Hasanipanah.

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Faradonbeh, R.S., Hasanipanah, M., Amnieh, H.B. et al. Development of GP and GEP models to estimate an environmental issue induced by blasting operation. Environ Monit Assess 190, 351 (2018). https://doi.org/10.1007/s10661-018-6719-y

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