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Evaluation of blast-induced ground vibration predictors

โœ Scribed by Manoj Khandelwal; T.N. Singh


Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
263 KB
Volume
27
Category
Article
ISSN
0267-7261

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Evaluation of blast-induced ground vibra
โœ Manoj Khandelwal; T.N. Singh ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 263 KB

The present paper mainly deals with the prediction of blast-induced ground vibration level at a Magnesite Mine in tecto-dynamically vulnerable hilly terrain in Himalayan region in India. The ground vibration was monitored to calculate the safe charge of explosive to avoid the continuous complaints f

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Prediction of vibration is very important in mining operations as well as civil engineering projects. In this paper, multi layer perceptron neural network (MLPNN), radial basis function neural network (RBFNN) and general regression neural network (GRNN) were utilized to predict ground vibration leve

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The aim of this study is to show the effect of geological factors in predicting the level of blast-induced ground vibrations. The sitespecific character of ground must be involved in the prediction models especially if the ground conditions have a variable character like in this case. But in a blast