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

被引：11
|
作者：
Bychkov, I. V. [1 ]
Vladimirov, D. Ya. [2 ]
Oparin, V. N. [3 ]
Potapov, V. P. [4 ,5 ]
Shokin, Yu. I.
机构：
[1] Russian Acad Sci, Siberian Branch, Matrosov Inst Syst Dynam & Control Theory, Ul Lermontova 134, Irkutsk 664033, Russia
[2] VIST Grp, Dokuchaev Per 3,Bld 1, Moscow 107078, Russia
[3] Russian Acad Sci, Siberian Branch, Chinakal Inst Min, Krasnyi Pr 54, Novosibirsk 630091, Russia
[4] Russian Acad Sci, Siberian Branch, Kemerovo Div Inst Computat Technol, Ul Rukavishnikova 21, Kemerovo 650025, Russia
[5] Russian Acad Sci, Siberian Branch, Inst Computat Technol, Pr Akad Lavrentieva 6, Novosibirsk 630090, Russia
来源：
JOURNAL OF MINING SCIENCE | 2016年 / 52卷 / 06期
关键词：
Big Data; intelligent analysis; computational and mini-clusters; raw data sets; geomechanical and geodynamic data flow computing; cloud computing; distributed computing; safe subsoil management; SIGN EXPLOSION RESPONSE; GEOINFORMATION SYSTEM; ENTROPY ANALYSIS; PENDULUM WAVES; AREAS; MIGRATION; POLLUTION; ROCKS; MINES;
D O I：
10.1134/S1062739116061747
中图分类号：
TD [矿业工程];
学科分类号：
0819 ;
摘要：
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.
引用
收藏
页码：1195 / 1209
页数：15
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