Bibliometric Analysis of Achievements on the Dam Safety Monitoring in SCI

Article Preview

Abstract:

In this work, bibliometric analysis was applied to evaluate global scientific production and developing trend of the dam safety monitoring research through Science Citation Index (SCI) papers with online version published as following aspects: publication outputs, subject categories, countries, institutes, citations, authorship and co-authorship, author key words and co-words analysis. Global literature of the dam safety monitoring research has increased rapidly over the past years and has boosted in recent years. The quantity and quality of papers in P.R. China are in a leading position. There is a very important new finding from the research focus that tailings dam has been adequately studied. With the further development of the dam safety monitoring research, it is presumed that scientists might concentrate mainly on safety prediction and health monitoring instead of simple safety monitoring.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2026-2033

Citation:

Online since:

January 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[19] Wu ZR 2003 SAFETY MONITORING TH V P.

Google Scholar

[15] Gu CS 2006 SAFETY MONITORING DA V P.

Google Scholar

[8] Ferretti A 2001 IEEE T GEOSCI REMOTE V39 P8.

Google Scholar

[7] Pytharouli SI 2005 ENG STRUCT V27 P361.

Google Scholar

[7] De Sortis A 2007 ENG STRUCT V29 P110.

Google Scholar

[6] Clements RP 1984 J GEOTECH ENG-ASCE V110 P821.

Google Scholar

[6] Hunter G 2003 J GEOTECH GEOENVIRON V129 P909.

Google Scholar

[5] Wu ZR 2007 SCI CHINA SER E V50 P34.

Google Scholar

[5] Wang FW 2004 LANDSLIDES V1 P157.

Google Scholar

[5] Szostak-chrzanowski A 2005 ENG GEOL V79 P3.

Google Scholar

[5] Wu ZR 1997 DAM SAFETY COMPREHEN V P Co-word analysis of the dam safety monitoring With the searches of Keyword and Term as network nodes by the information visualization software-CiteSpaceII to use co-word analysis to analyze 293 bibliographic literatures, it gets the frequency of keywords, which are the research focus. In order to get a more clear understanding of the research focus, it draws Tab. 3 to show the keyword (Freq ≥ 5). The clusters are Research content, Monitoring Project, Application and Methods. Tab. 3, Dam safety monitoring research areas important keywords Seq Freq Keyword Cluster Freq Freq Keyword.

DOI: 10.20944/preprints202304.0069.v1

Google Scholar

[1] 127 Dam safety monitoring Research content 212 127 Dam safety monitoring.

Google Scholar

[2] [42] Deformation monitoring.

Google Scholar

[42] Deformation monitoring.

Google Scholar

[3] [17] Tailings dam.

Google Scholar

[17] Tailings dam.

Google Scholar

[4] [12] Sar interferometry.

Google Scholar

[11] Prediction.

Google Scholar

[5] [11] Prediction.

Google Scholar

[10] Model.

Google Scholar

[6] [11] Sensor.

Google Scholar

[5] Health monitoring.

Google Scholar

[7] [10] Model Monitoring Project.

Google Scholar

[32] [10] Landslide.

Google Scholar

[8] [10] Landslide.

Google Scholar

[9] Settlement.

Google Scholar

[9] [9] Settlement.

Google Scholar

[7] Strain.

Google Scholar

[10] [7] Strain.

Google Scholar

[6] Displacement.

Google Scholar

[11] [6] Time series Application.

Google Scholar

[23] [12] Sar interferometry.

Google Scholar

[12] [5] Displacement.

Google Scholar

[11] Sensor.

Google Scholar

[13] [5] Health monitoring Methods.

Google Scholar

[16] [6] Time series.

Google Scholar

[14] [5] Statistical analysis.

Google Scholar

[1] Zhao Zhiren, Xu Rui. Advance and Prospect of Monitoring Technology for Dam Safety [J]. Hydropower Automation and Dam Monitoring, 2010, 34 (5): 52-57.

Google Scholar

[2] Qiu Junping, Information metrology [M]. Wuhan University Press, (2007).

Google Scholar

[3] Qiu Junping, Ma Ruimin, Li Yejun. Reconsiderations on Co-citation Analysis [J]. Journal of the China Society for Scientific and Technical Information, 2008, 27 (1): 69-74.

Google Scholar

[4] Zhang Han, Wang Xiaoyu, Cui Lei. Research on the Development Trend of Subject Domain by Combining Co-word Analysis Method with Cited Times of Documents [J]. Information Studies: Theory & Application, 2007, 30 (3): 378-380.

Google Scholar

[5] Zhao Rongying, Xu Limin. Bibliometrics to evolve the forefront of knowledge mapping and research Analysis [J]. Journal of Library Science in China, 2010, 36 (5): 60-68 (in Chinese).

Google Scholar

[6] Zhong Weijin, Li Jia. The Research of Co-word Analysis (1)—the Process and Methods of Co-word Analysis [J]. Journal of Information, 2008, 5: 70-72.

Google Scholar

[7] Chen, C. (2004) Searching for intellectual turning points: Progressive Knowledge Domain Visualization. Proc. Nat. Acad. Sci., 101 (Suppl. ): 5303-5310.

DOI: 10.1073/pnas.0307513100

Google Scholar

[8] Yu Guangming, Song Chuanwang, Wu Yanxia, etc. The New Development of Security Studies of Tailings Dam Abroad and the Development Tendency of Security Studies of Tailings Dam in Our Country [OL]. 2012, 03(13).

Google Scholar

[9] Zhao Zhijun, Yangao Wei, Xie Keming. Research on Safety Monitoring System of Tailing Dams [J]. Modern Electronic Technology, 2010, 5: 197-199.

Google Scholar

[10] Xu fun, Lang school governance, Pei Xin-cai, Xue Lixian based on fiber transmission tailings Security Monitoring and Early Warning System [J], gold, 2011, 32 (7): 43-47.

Google Scholar

[11] Wu Junru, Gu Chongshi. Dam Safety Evaluation Expert System [M]. Beijing Science and Technology Press, (1997).

Google Scholar

[12] Guo Tong. Progress of Health Monitoring [J]. International academic trends, 2008 (4): 26-27.

Google Scholar

[13] Zhang Jin-ping, Li Libing, Lu Zhengchao. Review and prospect of dam safety monitoring [J]. Journal of China Institute of Water Resources and Hydropower Research7-322.

Google Scholar