NDLI: Application of cuckoo search algorithm to estimate peak particle velocity in mine blasting

Content Provider	Springer Nature Link
Author	Fouladgar, Nazanin Hasanipanah, Mahdi Bakhshandeh Amnieh, Hassan
Copyright Year	2016
Abstract	Ground vibration is one of the most undesirable effects of blasting operation in surface mines. Therefore, it seems that the prediction of ground vibrations with a high degree of accuracy is necessary to reduce environmental effects. This article proposes a novel swarm intelligence algorithm based on cuckoo search (NSICS) to create a precise equation for predicting the ground vibration produced by blasting operations in Miduk copper mine, Iran. To evaluate the proposed NSICS model, several empirical equations were also utilized. In this regard, 85 blasting events were considered, and the values of two effective parameters on the ground vibration, namely, maximum charge used per delay and distance between blast face and monitoring station, were measured. In addition, the values of peck particle velocity (PPV), as a vibration descriptor, were recorded in each blasting. Two performance indices, i.e., root mean square error and coefficient of multiple correlation (R 2), were used to determine the performance capacity of the proposed models. Comparing the values predicted by the models demonstrated that the proposed equation by NSICS is more reliable than empirical equations in predicting the PPV.
Starting Page	181
Ending Page	189
Page Count	9
File Format	PDF
ISSN	01770667
Journal	Engineering with Computers
Volume Number	33
Issue Number	2
e-ISSN	14355663
Language	English
Publisher	Springer London
Publisher Date	2016-06-30
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Blasting operation Ground vibration Cuckoo search algorithm NSICS Computer-Aided Engineering (CAD, CAE) and Design Math. Applications in Chemistry Systems Theory, Control Calculus of Variations and Optimal Control; Optimization Classical Mechanics ApplicationMathematics/Computational Methods of Engineering
Content Type	Text
Resource Type	Article
Subject	Engineering Computer Science Applications Modeling and Simulation Software

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