Standard

Mining information science and Big Data concept for integrated safety monitoring in subsoil management. / Bychkov, I. V.; Vladimirov, D. Ya; Oparin, V. N. et al.

In: Journal of Mining Science, Vol. 52, No. 6, 01.11.2016, p. 1195-1209.

Research output: Contribution to journal › Article › peer-review

Harvard

Bychkov, IV, Vladimirov, DY, Oparin, VN, Potapov, VP & Shokin, YI 2016, 'Mining information science and Big Data concept for integrated safety monitoring in subsoil management', Journal of Mining Science, vol. 52, no. 6, pp. 1195-1209. https://doi.org/10.1134/S1062739116061747

APA

Bychkov, I. V., Vladimirov, D. Y., Oparin, V. N., Potapov, V. P., & Shokin, Y. I. (2016). Mining information science and Big Data concept for integrated safety monitoring in subsoil management. Journal of Mining Science, 52(6), 1195-1209. https://doi.org/10.1134/S1062739116061747

Vancouver

Bychkov IV, Vladimirov DY, Oparin VN, Potapov VP, Shokin YI. Mining information science and Big Data concept for integrated safety monitoring in subsoil management. Journal of Mining Science. 2016 Nov 1;52(6):1195-1209. doi: 10.1134/S1062739116061747

Author

Bychkov, I. V. ; Vladimirov, D. Ya ; Oparin, V. N. et al. / Mining information science and Big Data concept for integrated safety monitoring in subsoil management. In: Journal of Mining Science. 2016 ; Vol. 52, No. 6. pp. 1195-1209.

BibTeX

@article{feddf09e417b4edaa193e8b48aab24e3,
title = "Mining information science and Big Data concept for integrated safety monitoring in subsoil management",
abstract = "The discussed challenge and its prospects in mining geoinformation science are connected with Big Data concept—flows of large sets of various data on mining. The authors describe Big Data technology and its general implementation on mini-clusters using Hadoop and MapReduce with case studies presented.",
keywords = "Big Data, cloud computing, computational and mini-clusters, distributed computing, geomechanical and geodynamic data flow computing, intelligent analysis, raw data sets, safe subsoil management",
author = "Bychkov, {I. V.} and Vladimirov, {D. Ya} and Oparin, {V. N.} and Potapov, {V. P.} and Shokin, {Yu I.}",
year = "2016",
month = nov,
day = "1",
doi = "10.1134/S1062739116061747",
language = "English",
volume = "52",
pages = "1195--1209",
journal = "Journal of Mining Science",
issn = "1062-7391",
publisher = "Springer New York",
number = "6",

}

RIS

TY - JOUR

T1 - Mining information science and Big Data concept for integrated safety monitoring in subsoil management

AU - Bychkov, I. V.

AU - Vladimirov, D. Ya

AU - Oparin, V. N.

AU - Potapov, V. P.

AU - Shokin, Yu I.

PY - 2016/11/1

Y1 - 2016/11/1

N2 - The discussed challenge and its prospects in mining geoinformation science are connected with Big Data concept—flows of large sets of various data on mining. The authors describe Big Data technology and its general implementation on mini-clusters using Hadoop and MapReduce with case studies presented.

AB - The discussed challenge and its prospects in mining geoinformation science are connected with Big Data concept—flows of large sets of various data on mining. The authors describe Big Data technology and its general implementation on mini-clusters using Hadoop and MapReduce with case studies presented.

KW - Big Data

KW - cloud computing

KW - computational and mini-clusters

KW - distributed computing

KW - geomechanical and geodynamic data flow computing

KW - intelligent analysis

KW - raw data sets

KW - safe subsoil management

UR - http://www.scopus.com/inward/record.url?scp=85029036447&partnerID=8YFLogxK

U2 - 10.1134/S1062739116061747

DO - 10.1134/S1062739116061747

M3 - Article

AN - SCOPUS:85029036447

VL - 52

SP - 1195

EP - 1209

JO - Journal of Mining Science

JF - Journal of Mining Science

SN - 1062-7391

IS - 6

ER -

ID: 25324387