NDLI: Intelligent systems for ground vibration measurement: a comparative study

Content Provider	Springer Nature Link
Author	Verma, A. K. Singh, T. N.
Copyright Year	2010
Abstract	This paper deals with the application of genetic algorithm (GA) optimization technique to predict peak particle velocity (PPV). PPV is one of the important parameters to be determined to minimize the damage caused by ground vibration. A number of previous researchers have tried to use different empirical methods to predict PPV but these empirical methods have their limitations due to their less versatile application. In this paper, GA technique is used for the prediction of PPV by incorporating blast design and explosive parameters and the suitability of one technique over other has been analyzed based on the results. Datasets have been obtained from one of the Kurasia mines. 127 data sets were used to establish GA architecture and 10 data sets have been used for validation of GA model to observe its prediction capability. The results obtained have been compared with different traditional vibration predictors, multivariate regression analysis, artificial neural network and the superiority of application of GA over previous methodology have been discussed. The mean absolute percentage error in the proposed architect is very low (0.08) as compared to other predictors.
Starting Page	225
Ending Page	233
Page Count	9
File Format	PDF
ISSN	01770667
Journal	Engineering with Computers
Volume Number	27
Issue Number	3
e-ISSN	14355663
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-07-07
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Peak particle velocity Genetic algorithm ANN Ground vibration P-wave S-wave Computer-Aided Engineering (CAD, CAE) and Design Math. Applications in Chemistry Systems Theory, Control Mechanics Calculus of Variations and Optimal Control; Optimization ApplicationMathematics/Computational Methods of Engineering
Content Type	Text
Resource Type	Article
Subject	Engineering Computer Science Applications Modeling and Simulation Software

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