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Prediction of Blast-Induced Flyrock in Opencast Mines Using ANN and ANFIS

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Title Prediction of Blast-Induced Flyrock in Opencast Mines Using ANN and ANFIS
 
Creator TRIVEDI, R
SINGH, TN
GUPTA, N
 
Subject ARTIFICIAL NEURAL-NETWORKS
FUZZY INFERENCE SYSTEM
PERFORMANCE PREDICTION
COMPRESSIVE STRENGTH
AREA SECURITY
ROCK
MODEL
SETS
Artificial neural network
Adaptive neuro fuzzy inference system
Blasting
Opencast mining
Flyrock distance
 
Description The aim of present study is prediction of blast-induced flyrock distance in opencast limestone mines using artificial intelligence techniques such as artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS). Blast design and geotechnical variables such as linear charge concentration, burden, stemming length, specific charge, unconfined compressive strength, and rock quality designation have been selected as independent variables and flyrock distance has been used as dependent variable. Blasts required for the study purpose have been conducted in four limestone mines in India. Out of one hundred and twenty-five (125) blasts, dataset of one hundred blasts have been used for training, testing and validation of the ANN and ANFIS based prediction model. Twenty-five (25) data have been used for evaluation of the trained ANN and ANFIS models. In order to know the relationship among the independent and dependent variables, multi-variable regression analysis (MVRA) has also been performed. The performance indices such as root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R-2) have been evaluated for ANN, ANFIS and MVRA. RMSE as well as MAE have been found lower and R-2 has been found higher in case of ANFIS in comparison of ANN and MVRA. ANFIS has been found a superior predictive technique in comparison to ANN and MVRA. Sensitivity analysis has also been performed using ANFIS to assess the impact of independent variables on flyrock distance.
 
Publisher SPRINGER
 
Date 2016-01-14T12:04:14Z
2016-01-14T12:04:14Z
2015
 
Type Article
 
Identifier GEOTECHNICAL AND GEOLOGICAL ENGINEERING, 33(4)875-891
0960-3182
1573-1529
http://dx.doi.org/10.1007/s10706-015-9869-5
http://dspace.library.iitb.ac.in/jspui/handle/100/17450
 
Language en