Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data

In the age of big data, the prediction and evaluation of geological mineral resources have gradually entered a new stage, intelligent prospecting. This review briefly summarizes the research development of textual data mining and spatial data mining. It is considered that the current research on min...

Full description

Bibliographic Details
Main Authors: Shi Li, Jianping Chen, Chang Liu
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Minerals
Subjects:
Online Access:https://www.mdpi.com/2075-163X/12/5/616
_version_ 1797497573069553664
author Shi Li
Jianping Chen
Chang Liu
author_facet Shi Li
Jianping Chen
Chang Liu
author_sort Shi Li
collection DOAJ
description In the age of big data, the prediction and evaluation of geological mineral resources have gradually entered a new stage, intelligent prospecting. This review briefly summarizes the research development of textual data mining and spatial data mining. It is considered that the current research on mineral resource prediction has integrated logical reasoning, theoretical models, computational simulations, and other scientific research models, and has gradually advanced toward a new model. This type of new model has tried to mine unknown and effective knowledge from big data by intelligent analysis methods. However, many challenges have come forward, including four aspects: (i) discovery of prospecting big data based on geological knowledge system; (ii) construction of the conceptual prospecting model by intelligent text mining; (iii) mineral prediction by intelligent spatial big data mining; (iv) sharing and visualization of the mineral prediction data. By extending the geological analysis in the process of prospecting prediction to the logical rules associated with expert knowledge points, the theory and methods of intelligent mineral prediction were preliminarily established based on geological big data. The core of the theory is to promote the flow, invocation, circulation, and optimization of the three key factors of “knowledge”, “model”, and “data”, and to preliminarily constitute the prototype of intelligent linkage mechanisms. It could be divided into four parts: intelligent datamation, intelligent informatization, intelligent knowledgeization, and intelligent servitization.
first_indexed 2024-03-10T03:21:08Z
format Article
id doaj.art-6f30600cd28e461a91c275ab9e18e6cd
institution Directory Open Access Journal
issn 2075-163X
language English
last_indexed 2024-03-10T03:21:08Z
publishDate 2022-05-01
publisher MDPI AG
record_format Article
series Minerals
spelling doaj.art-6f30600cd28e461a91c275ab9e18e6cd2023-11-23T12:19:29ZengMDPI AGMinerals2075-163X2022-05-0112561610.3390/min12050616Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big DataShi Li0Jianping Chen1Chang Liu2Department of Big Data, School of Information, Beijing Wuzi University, Beijing 101149, ChinaDepartment of Remote Sensing and Geo-Information, School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, ChinaDepartment of Remote Sensing and Geo-Information, School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, ChinaIn the age of big data, the prediction and evaluation of geological mineral resources have gradually entered a new stage, intelligent prospecting. This review briefly summarizes the research development of textual data mining and spatial data mining. It is considered that the current research on mineral resource prediction has integrated logical reasoning, theoretical models, computational simulations, and other scientific research models, and has gradually advanced toward a new model. This type of new model has tried to mine unknown and effective knowledge from big data by intelligent analysis methods. However, many challenges have come forward, including four aspects: (i) discovery of prospecting big data based on geological knowledge system; (ii) construction of the conceptual prospecting model by intelligent text mining; (iii) mineral prediction by intelligent spatial big data mining; (iv) sharing and visualization of the mineral prediction data. By extending the geological analysis in the process of prospecting prediction to the logical rules associated with expert knowledge points, the theory and methods of intelligent mineral prediction were preliminarily established based on geological big data. The core of the theory is to promote the flow, invocation, circulation, and optimization of the three key factors of “knowledge”, “model”, and “data”, and to preliminarily constitute the prototype of intelligent linkage mechanisms. It could be divided into four parts: intelligent datamation, intelligent informatization, intelligent knowledgeization, and intelligent servitization.https://www.mdpi.com/2075-163X/12/5/616the fourth paradigmgeological big dataprospecting predictionintelligent algorithm
spellingShingle Shi Li
Jianping Chen
Chang Liu
Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
Minerals
the fourth paradigm
geological big data
prospecting prediction
intelligent algorithm
title Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
title_full Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
title_fullStr Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
title_full_unstemmed Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
title_short Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
title_sort overview on the development of intelligent methods for mineral resource prediction under the background of geological big data
topic the fourth paradigm
geological big data
prospecting prediction
intelligent algorithm
url https://www.mdpi.com/2075-163X/12/5/616
work_keys_str_mv AT shili overviewonthedevelopmentofintelligentmethodsformineralresourcepredictionunderthebackgroundofgeologicalbigdata
AT jianpingchen overviewonthedevelopmentofintelligentmethodsformineralresourcepredictionunderthebackgroundofgeologicalbigdata
AT changliu overviewonthedevelopmentofintelligentmethodsformineralresourcepredictionunderthebackgroundofgeologicalbigdata