DETERMINATION OF THE NUMBER OF SEISMOTECTONIC PROVINCES USING PARTITIONING CLUSTERING OF SEISMIC DATA

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

KAZEMI BEYDOKHTI MOHAMMAD; ABBASPOUR RAHIM ALI

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY Year:2015 | Volume:3 | Issue:1 Page(s): 1-14

Download Full-Text

Persian Verion

View:

956

Download:

Cites:

Information Journal Paper

Title

DETERMINATION OF THE NUMBER OF SEISMOTECTONIC PROVINCES USING PARTITIONING CLUSTERING OF SEISMIC DATA

Author(s)

KAZEMI BEYDOKHTI MOHAMMAD | ABBASPOUR RAHIM ALI | Issue Writer Certificate

Keywords

SEISMOTECTONIC ZONESQ2

CLUSTERINGQ2

VALIDITY INDEXESQ2

SEISMIC DATAQ2

Abstract

Seismotectonic provinces are defined as areas that have similar seismological characteristics, active tectonic fault system similar to each other. Identification of these areas is one of the most important subjects in seismic hazard analysis. CLUSTERING methods are known as techniques for identifying information associated with the huge number of data. Since these methods are appropriate visual representations and provide reliable results, they can be an important tool for determining the seismotectonic provinces. In this study, three partitioning CLUSTERING methods were used including: K-means, CALARA, and Fuzzy C-means. For assessing the validity of these methods, five CLUSTERING VALIDITY INDEXES including: Davies-Bouldin, Silhouette, SD, S_Dbw, and Xie-Beni were used. Parameters including the earthquake epicenters, magnitude, gravity, magnetism, and fault density, as input CLUSTERING methods, were considered for modeling seismotectonic regions. After determining the optimal number of clusters, in order to evaluate the results of CLUSTERING model IRCOLD seismotectonic model was applied. The results showed that compared with other methods, CLARA have a greater compatibility with seismotectonic model in Iran. Finally, after comparing the number of optimized CLUSTERING methods with seismotectonic model it is concluded that the best number of seismotectonic provinces is 13.

Cites

No record.

References

No record.

Cite

APA: Copy

KAZEMI BEYDOKHTI, MOHAMMAD, & ABBASPOUR, RAHIM ALI. (2015). DETERMINATION OF THE NUMBER OF SEISMOTECTONIC PROVINCES USING PARTITIONING CLUSTERING OF SEISMIC DATA. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, 3(1), 1-14. SID. https://sid.ir/paper/230119/en

Vancouver: Copy

KAZEMI BEYDOKHTI MOHAMMAD, ABBASPOUR RAHIM ALI. DETERMINATION OF THE NUMBER OF SEISMOTECTONIC PROVINCES USING PARTITIONING CLUSTERING OF SEISMIC DATA. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY[Internet]. 2015;3(1):1-14. Available from: https://sid.ir/paper/230119/en

IEEE: Copy

MOHAMMAD KAZEMI BEYDOKHTI, and RAHIM ALI ABBASPOUR, “DETERMINATION OF THE NUMBER OF SEISMOTECTONIC PROVINCES USING PARTITIONING CLUSTERING OF SEISMIC DATA,” ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, vol. 3, no. 1, pp. 1–14, 2015, [Online]. Available: https://sid.ir/paper/230119/en

Related Journal Papers