Prediction of flyrock throw distance in quarries by variable selection procedures and ANFIS modelling technique

Turker Hudaverdi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


This study suggests application of variable reduction procedures for flyrock prediction. It was aimed to create robust and non-complex predictive models. Eleven operational blast parameters and rock mass properties were measured in an aggregate quarry. Dominant parameters for flyrock occurrence were determined by multivariate statistical methods. Two parallel ANFIS models were developed for flyrock prediction. The first ANFIS model was constructed based on the results of stepwise regression. Burden–hole diameter ratio, in-situ block size and specific charge are the input parameters of ANFIS 1. The second ANFIS model was created based on the results obtained by factor analysis. Burden–hole diameter ratio, bench height–burden ratio, number of holes and charge weight are used as input parameters for ANFIS 2. The calculated mean absolute percentage errors are lower than eight percent for the ANFIS predictions. The median absolute errors are lower than 5 m. The study also investigates alternative accuracy measures to evaluate forecasting performance. Standardized errors, normalized errors and Nash–Sutcliffe Efficiency were found to be useful for model validation. It is concluded that more than a single model can be created for a specific site. Pre-statistical analysis for variable reduction increases performance of the predictive models. Burden appeared to be a significant parameter for flyrock throw.

Original languageEnglish
Article number281
JournalEnvironmental Earth Sciences
Issue number10
Publication statusPublished - May 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.


This study was partially supported by the Research Fund of the Istanbul Technical University (No: MGA-2017-40581). The author is grateful to the Istanbul Technical University for their financial support.

FundersFunder number
Istanbul Teknik ÜniversitesiMGA-2017-40581


    • Accuracy measures
    • Aggregate quarry
    • ANFIS
    • Burden
    • Factor analysis
    • Flyrock


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