APPLICATION OF SOM NEURAL NETWORK FOR NUMERICAL TECTONIC ZONING: A NEW APPROACH FOR TECTONIC ZONING OF IRAN

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.

ZAMANI AHMAD; NEDAEI MAHNAZ

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

Journal Paper

Paper Information

Journal: GEOSCIENCES Year:2010 | Volume:19 | Issue:75 Page(s): 83-88

Download Full-Text

Persian Verion

View:

1,121

Download:

Cites:

Information Journal Paper

Title

APPLICATION OF SOM NEURAL NETWORK FOR NUMERICAL TECTONIC ZONING: A NEW APPROACH FOR TECTONIC ZONING OF IRAN

Author(s)

ZAMANI AHMAD | NEDAEI MAHNAZ | Issue Writer Certificate

Keywords

TECTONIC ZONINGQ3

CLUSTERINGQ2

SELF-ORGANIZING MAPQ3

NEURAL NETWORKQ3

Abstract

One of the basic discussions in geosciences is construction of different TECTONIC ZONING maps. In conventional TECTONIC ZONING, not only the great amounts of subjective judgment are involved but also accurate interpretation of high-dimensional data is so difficult and out of human capability. To alleviate these deficiencies, quantitative scientific methods in data mining domain can be applied as an effective and useful tool to construct the new numerical maps in geosciences. In this paper SELF-ORGANIZING MAP.(SOM) NEURAL NETWORK that is one of the common methods in data mining has been applied for numerical TECTONIC ZONING of Iran. SOM is an unsupervised artificial NEURAL NETWORK particularly adept at pattern recognition and CLUSTERING of high-dimensional data. Visualization of high-dimensional data in two-dimensional topological-preserving feature map is another specific capability of SOM that represent both homogeneity within and similarity between clusters. Although there are some similarities between SOM's numerical maps constructed here and the conventional maps but SOM method is more powerful for identification and interpretation of different zones than conventional methods. Utilizing SOM method enables us not only to evaluate the degree of homogeneity in each zone, but also to separate regions zone that experience similar geological evolutionary despite of their geographical locations. For instance Lut and Gavkhuni zones show more homogeneity than Makran and Azerbayejan zones also Kopeh-Dagh and Zagros are located at different regions, they have similar features. The results obtained here represent separation between Makran from East Iranian Ranges and Western Azerbaijan from Alborz Ranges, too. It is important to recognize that the SOM's results are based purely on the geophysical, geological and seismic features presented previously. So correspondences and differences between the SOM's zones and a given zone based on conventional method must receive careful thought.

Cites

No record.

References

No record.

Cite

APA: Copy

ZAMANI, AHMAD, & NEDAEI, MAHNAZ. (2010). APPLICATION OF SOM NEURAL NETWORK FOR NUMERICAL TECTONIC ZONING: A NEW APPROACH FOR TECTONIC ZONING OF IRAN. GEOSCIENCES, 19(75), 83-88. SID. https://sid.ir/paper/31271/en

Vancouver: Copy

ZAMANI AHMAD, NEDAEI MAHNAZ. APPLICATION OF SOM NEURAL NETWORK FOR NUMERICAL TECTONIC ZONING: A NEW APPROACH FOR TECTONIC ZONING OF IRAN. GEOSCIENCES[Internet]. 2010;19(75):83-88. Available from: https://sid.ir/paper/31271/en

IEEE: Copy

AHMAD ZAMANI, and MAHNAZ NEDAEI, “APPLICATION OF SOM NEURAL NETWORK FOR NUMERICAL TECTONIC ZONING: A NEW APPROACH FOR TECTONIC ZONING OF IRAN,” GEOSCIENCES, vol. 19, no. 75, pp. 83–88, 2010, [Online]. Available: https://sid.ir/paper/31271/en

Related Journal Papers