Application of Intelligent Models for Flyrock Prediction Considering Design Parameters and Bench Face Characteristics

Turker Hudaverdi*, Yasar Agan

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Araştırma sonucu: ???type-name???Makalebilirkişi

Özet

This study tries to predict blast-induced flyrock using intelligent modelling techniques. Flyrock is a site-specific phenomenon. Design variables and rock properties highly influence flyrock throw distance. Site investigations were conducted in a sandstone quarry. Fundamental operational parameters, blast dimensions, bench face condition, and rock mass structure were monitored. Stepwise regression technique was applied for variable selection. Burden–hole diameter ratio, in situ block size, and powder factor were determined as the most significant parameters. Considering output of stepwise regression, artificial neural network, ANFIS, and Gaussian process regression techniques were applied to predict flyrock throw. A comprehensive validation was performed using twelve different performance indices. Pre-determination of input parameters supported development of successful soft computing applications. Rock block size was found to be an appropriate input variable for flyrock modelling. In addition to classical performance indices, standardized and symmetric accuracy metrics were quite useful in model validation process. The intelligent models predict flyrock range with an error less than 6 m. The mean percentage errors are lower than 10%. ANFIS seems to be the best model for flyrock prediction. The calculated mean absolute error is 5.36 for ANFIS model.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)2331-2347
Sayfa sayısı17
DergiMining, Metallurgy and Exploration
Hacim40
Basın numarası6
DOI'lar
Yayın durumuYayınlandı - Ara 2023

Bibliyografik not

Publisher Copyright:
© 2023, Society for Mining, Metallurgy & Exploration Inc.

Finansman

This study was partly supported by the Research Fund of the Istanbul Technical University (project name: The effects of the variations in blast design and initiation systems on blast induced ground vibrations. No: 38511).

FinansörlerFinansör numarası
Ulusal Yüksek Başarımlı Hesaplama Merkezi, Istanbul Teknik Üniversitesi
Istanbul Teknik Üniversitesi
Bilimsel Araştırma Projeleri Birimi, İstanbul Teknik Üniversitesi38511

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