Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network-Reference-Cited by-同舟云学术

Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network

Published:2019-03-01 Issue:2 Volume:29 Page:691-709
ISSN:1520-7439
Container-title:Natural Resources Research
language:en
Short-container-title:Nat Resour Res

Author:

Nguyen Hoang^ORCID,Drebenstedt Carsten,Bui Xuan-Nam,Bui Dieu Tien

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science

Link

http://link.springer.com/content/pdf/10.1007/s11053-019-09470-z.pdf

Reference80 articles.

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2. Ak, H., & Konuk, A. (2008). The effect of discontinuity frequency on ground vibrations produced from bench blasting: A case study. Soil Dynamics and Earthquake Engineering,28(9), 686–694.

3. Ambraseys, N. R., & Hendron, A. J. (1968). Dynamic behavior of rock masses. In K. G. Stagg & O. C. Zienkievicz (Eds.), Rock mechanics in engineering practice (pp. 203–207). London: John Wiley and Sons.

4. Amiri, M., Amnieh, H. B., Hasanipanah, M., & Khanli, L. M. (2016). A new combination of artificial neural network and k-nearest neighbors models to predict blast-induced ground vibration and air-overpressure. Engineering with Computers,32(4), 631–644.

5. Arai, K., & Barakbah, A. R. (2007). Hierarchical k-means: An algorithm for centroids initialization for k-means. Reports of the Faculty of Science and Engineering,36(1), 25–31.

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