Ahmad Zamani; M. Nedaei
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 ...
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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 EastIranianRanges and Western Azerbaijan from AlborzRanges, 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.
B. Tokhmechi; H. Memarian; H. Ahmadi Noubari; B. Moshiri
Abstract
Joint study is one of the primary jobs in many geological, mining, geotechnical and petroleum exploration projects. Up to 10 features of joints are gathered during each field survey, while only two of them (dip and dip direction) are normally used to classify these complex features. This paper proposes ...
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Joint study is one of the primary jobs in many geological, mining, geotechnical and petroleum exploration projects. Up to 10 features of joints are gathered during each field survey, while only two of them (dip and dip direction) are normally used to classify these complex features. This paper proposes a new method for joint set classification which can use more than two surveyed features. A synthetic set of 8 joint set, each joint defined with 4 features (dip, dip direction, type of infilling and amount of infilling), created in a way that with two features (dip and dip direction) sets could not be differentiated. Necessary program developed to use Bayesian classifier to sort 8 synthetic joint sets in 4D space. Present study showed that all 8 sets can be successfully differentiated by using Bayesian method.
