A New Approach for Border Detection of the Dumluca (Turkey) Iron Ore Area: Wavelet Cellular Neural Networks |
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Authors: | A Muhittin Albora Abdullah Bal Osman N Ucan |
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Institution: | (1) Engineering Faculty, Geophysical Department, Istanbul University, 34320 Avcilar, Istanbul, Turkey;(2) Electrical and Electronics Faculty, Department of Electrical Engineering, Yildiz Technical University, 80750 Besiktas, Istanbul, Turkey;(3) Engineering Faculty, Electrical and Electronics Department, Istanbul University, 34320 Avcilar, Istanbul, Turkey |
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Abstract: | Anomaly analysis is used for various geophysics applications such as determination of geophysical structure's location and
border detections. Besides the classical geophysical techniques, artificial intelligence based image processing algorithms
have been found attractive for geophysical anomaly analysis. Recently, cellular neural networks (CNN) have been applied to
geophysical data and satisfactory results are reported. CNN provides fast and parallel computational capability for geophysical
image processing applications due to its filtering structure. The behavior of CNN is defined by two template matrices that
are adjusted by a properly supervised learning algorithm. After training stage for geophysical data, Bouguer anomaly maps
can be processed and analyzed sequentially. In this paper, CNN learning and processing capability have been improved, combining
Wavelet functions and backpropagation learning algorithms. The new architecture is denoted as Wavelet-Cellular Neural networks
(Wave-CNN) and it is employed to analyze Bouguer anomaly maps which are important to extract useful information in geophysics.
At first, Wave-CNN performance is tested on synthetic geophysical data, which are created by a computer environment. Then,
Bouguer anomaly maps of the Dumluca iron ore field have been analyzed and results are reported in comparison to real drilling
results. |
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Keywords: | Bouguer anomaly maps border detection cellular neural network wavelet backpropagation Dumluca ion ore |
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