Open AccessApplication of self organizing map in construction, geology and petroleum industry
Author(s) -
Tung Son Pham,
Huy Minh Truong,
Tuan Ba Pham
Publication year - 2017
Publication title -
khoa học công nghệ
Language(s) - English
Resource type - Journals
ISSN - 1859-0128
DOI - 10.32508/stdj.v20ik4.1110
Subject(s) - cluster analysis , self organizing map , petroleum industry , subject (documents) , industrial revolution , geology , artificial intelligence , computer science , mining engineering , construction engineering , engineering , geography , archaeology , paleontology , library science
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.