Exploration
reza Shahnavehsi; Farnusch Hajizadeh
Abstract
The present work is mainly about a method for illustrating the relation between the raw data in the same time; clustering is a key procedure to solve the problem of data division; also illustrating the connection among the elements of the research area simultaneously is important. Therefore, we propose ...
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The present work is mainly about a method for illustrating the relation between the raw data in the same time; clustering is a key procedure to solve the problem of data division; also illustrating the connection among the elements of the research area simultaneously is important. Therefore, we propose a novel kind of clustering for data mining in the gravity field to reach the presenting connection among all elements in the same time. For this research work, 867 gravity surveying points were collected in the southern part of Iran (near diapir of Larestan) with a range of absolute gravity from 978579.672 to 978981.186. In this paper, clustering by self-organizing- maps, by utilizing scatter plot matrix is utilized for detecting the relation between the easting, northing, elevation, and absolute gravity simultaneously. In the proposed method, the relations between arrays, two by two, are defined, and like matrix, each raw and column has different i and j values, which represent elements of the studied area, instead of number; for example, array A23 is data division between i = 2 or raw two (in our case northing) and j = 3 or column, three (in our case elevation). In this algorithm, firstly, by using self-organizing maps, clustering is done, and this processing is generated to all arrays by scatter plot matrix, and in all arrays, three clusters are proposed; the result of this clustering shows that in arrays A12, A13, A14, A21, A23, A24, A31, A32, A41, A42, clustering is performed perfectly, and the relationship between the parameters of the studied area near Larestan salt, diaper, can be useful in notifying the properties of this salt diapir.
Exploitation
Moslem Jahantigh; Hamidreza Ramazi
Abstract
Various methods have been used for clustering big data. Pattern recognition methods are suitable methods for clustering these data. Due to the large volume of samples taken in the drilling of mines and their analysis for various elements, this category of geochemical data can be considered big data. ...
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Various methods have been used for clustering big data. Pattern recognition methods are suitable methods for clustering these data. Due to the large volume of samples taken in the drilling of mines and their analysis for various elements, this category of geochemical data can be considered big data. Examining and evaluating drilling data in the Lar copper mine in Sistan and Baluchistan province located in the southeast of Iran requires the use of these methods. Therefore, the main goal of the article is the clustering of the drilling data in the mentioned mine and its zoning of the geochemical data. To achieve this goal, 3500 samples taken from drilling cores have been used. Elemental analysis for six elements has been done using the ICP-Ms method. Pattern recognition methods including SOM and K-MEANS have been used to evaluate the relation between these elements. The silhouette method has been used to determine and evaluate the number of clusters. Using this method, 4 clusters have been considered for the mentioned data. According to this method, it was found that the accuracy of clustering is higher in the SOM method. By considering the 4 clusters, 4 zones were identified using clustering methods. By comparing the results of the two methods and using the graphical method, it was determined that the SOM method has a better performance for clustering geochemical data in the studied area. Based on that, zones 2 and 4 were recognized as high-grade zones in this area.
D. Mohammadi; R. Mikaeil; J. Abdollahei Sharif
Abstract
The blasting method is one of the most important operations in most open-pit mines that has a priority over the other mechanical excavation methods due to its cost-effectiveness and flexibility in operation. However, the blasting operation, especially in surface mines, imposes some environmental problems ...
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The blasting method is one of the most important operations in most open-pit mines that has a priority over the other mechanical excavation methods due to its cost-effectiveness and flexibility in operation. However, the blasting operation, especially in surface mines, imposes some environmental problems including the ground vibration as one of the most important ones. In this work, an evaluation system is provided to study and select the best blasting pattern in order to reduce the ground vibration as one of the hazards in using the blasting method. In this work, 45 blasting patterns used for the Sungun copper mine are studied and evaluated to help determine the most suitable and optimum blasting pattern for reducing the ground vibration. Additionally, due to the lack of certainty in the nature of ground and the analyses relating to this drilling system, in the first step, a combination of the imperialist competitive algorithm and k-means algorithm is used for clustering the measured data. In the second step, one of the multi-criteria decision-making methods, namely TOPSIS (Technique for Order Performance by Similarity to Ideal Solution), is used for the final ranking. Finally, after evaluating and ranking the studied patterns, the blasting pattern No. 27 is selected. This pattern is used with the properties including a hole diameter of 16.5 cm, number of holes of 13, spacing of 4 m, burden of 3 m, and ammonium nitrate fuel oil of 1100 Kg as the most appropriate blasting pattern leading to the minimum ground vibration and reduction of damages to the environment and structures constructed around the mine.
