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Application of self organizing map in construction, geology and petroleum industry

Tung Son Pham 1, *
Huy Minh Truong 1
Tuan Ba Pham 1
  1. Faculty of Geology and Petroleum Engineering, Ho Chi Minh city University of Technology – VNU-HCM
Correspondence to: Tung Son Pham, Faculty of Geology and Petroleum Engineering, Ho Chi Minh city University of Technology – VNU-HCM. Email: pvphuc@vnuhcm.edu.vn.
Volume & Issue: Vol. 20 No. K4 (2017) | Page No.: 30-38 | DOI: 10.32508/stdj.v20iK4.1110
Published: 2017-07-31

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Copyright The Author(s) 2023. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

In recent years, Artificial Intelligence (AI) has become an emerging subject and been recognized as the flagship of the Fourth Industrial Revolution. AI is subtly growing and becoming vital in our daily life. Particularly, Self-Organizing Map (SOM), one of the major branches of AI, is a useful tool for clustering data and has been applied successfully and widespread in various aspects of human life such as psychology, economic, medical and technical fields like mechanical, construction and geology. In this paper, the primary purpose of the authors is to introduce SOM algorithm and its practical applications in geology and construction. The results are classification of rock facies versus depth in geology and clustering two sets of construction prices indices and building material costs indice.

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