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Neural Computing and Applications

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01.02.2016 | Original Article

Prediction of flyrock launch velocity using artificial neural networks

verfasst von: Saša Stojadinović, Nikola Lilić, Ivan Obradović, Radoje Pantović, Miodrag Denić

Erschienen in: Neural Computing and Applications | Ausgabe 2/2016

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Abstract

Due to a potential to cause damage to machinery and structures and cause injuries to personnel, flyrock is the most dangerous adverse effect of blasting operations. Because of that, it is of primary importance to predict flyrock events and maximum range of flyrock fragments in order to define safety limits and secure the perimeter. There are various models for flyrock range prediction, and most of them rely on proper calculations of flyrock launch velocity. However, a unique and universally applicable model of launch velocity prediction still does not exist. Work presented in this article is a concept of adaptive system application for the prediction of flyrock launch velocities. It shows the principles of input data selection, acquisition and processing and presents the principles of design, training, validation and verification of applied artificial neural network.

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Titel: Prediction of flyrock launch velocity using artificial neural networks
verfasst von: Saša Stojadinović
Nikola Lilić
Ivan Obradović
Radoje Pantović
Miodrag Denić
Publikationsdatum: 01.02.2016
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 2/2016
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-015-1872-5

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