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Application of K-Means algorithm to classify geochemical populations in Vein-type copper deposit in 1:100,000 sheet of Kariz now, Khorasan, Iran

Publish Year: 1403
Type: Conference paper
Language: English
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EMGBC08_047

Index date: 5 October 2024

Application of K-Means algorithm to classify geochemical populations in Vein-type copper deposit in 1:100,000 sheet of Kariz now, Khorasan, Iran abstract

TO address the challenge of limited access to mineral resources, this research utilizes a combination of dimensionality reduction techniques and sophisticated machine learning methods to significantly improve the accuracy and speed of detecting geochemical anomalies within stream sediments. The focus is particularly on the Razavi Khorasan province in northeastern Iran. The approach begins with Principal Component Analysis (PCA), applied after initial data preprocessing and the creation of a catchment basin incorporating associated values. Following PCA, the study employs K-Means, an unsupervised clustering algorithm, to categorize geochemical values into meaningful groups. This methodology uses preliminary data processing via correlation matrices and dimensionality reduction, followed by application of K-Means clustering on centered log-ratio transformed values of chosen elements. Through this computational model, the research effectively classifies stream sediment samples into three distinct clusters, offering a deeper insight into the areas geological features and the identification of possible mineral reserves responsing te the need to understand geochemical halos in a more accurate way.

Application of K-Means algorithm to classify geochemical populations in Vein-type copper deposit in 1:100,000 sheet of Kariz now, Khorasan, Iran Keywords:

Application of K-Means algorithm to classify geochemical populations in Vein-type copper deposit in 1:100,000 sheet of Kariz now, Khorasan, Iran authors

Maryam Shirjang

Master’s student at Amirkabir University of Technology

Abbas Moghsoudi

Associate Professor at Amirkabir University of Technology

Reza Ghezelbash

Assistant Professor at University of Tehran