A Mining Technology Collaboration Platform Theory and Its Product Development and Application to Support China’s Digital Mine Construction

Wang, Jinmiao; Bi, Lin; Wang, Liguan; Jia, Mingtao; Du, Mao

doi:10.3390/app9245373

Cited by 18 publications

(12 citation statements)

References 30 publications

(29 reference statements)

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“…In order to realise data storage, preliminary analysis, data cleaning, and even initial data visualisation, information systems are developed through the integration of correlated data procedures [157], [159], [162]. Considering various requirements of the system, different platforms are developed, such as gas monitoring and dynamic alarming system, air quality pollution monitoring, deformation and risk monitoring, etc.…”

Section: A Data Management and Information Systemsmentioning

confidence: 99%

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

et al. 2023

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Mining digitalisation have been receiving significant attention due to the utilisation of advanced technologies, such as IoT, automation, and sensing. However, maximising the potential value of collected data in the mining industry remains a challenge. Therefore, this paper aims to review timely concern topics to facilitate the fusion implementation in mining engineering. Specifically, this review covers recent popular topics, such as, data visualisation, data management, data analytics, data fusion, visual analytics, and mining digital twin construction. In this paper, we aim to draw a comprehensive picture about the fusion of data visualisation and analytics in the big data context, by examining the recent academic research related to these topics. Therefore, this paper reviews the visualisation domain by conventional classification, including scientific visualisation, information visualisation, and visual analytics, associated with the analysis of current digital twin development. Next, according to the challenges and issues related to visualisation development, this paper reviews the data management and data analytics domains as well. Incorporating with the fusion concept, machine learning-oriented fusion applications and potential scenarios in the mining industry have been discussed. In addition, based on the observation across various domains, this paper presents challenges and future potentials of data fusion in mining.INDEX TERMS mining digitalisation, data management, data analytics, data visualisation, and data fusion I. INTRODUCTION

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Section: A Data Management and Information Systemsmentioning

confidence: 99%

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

et al. 2023

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“…Many companies have seized upon this development opportunity to conduct overseas mergers, acquisitions, and cooperative investments [15]. The same is true for mining companies; the group's mines are gradually spreading across the world, and the scale of the company is expanding, but the organizational structure and operating methods are still traditional, making management and coordination difficult [16,17]. Specifically:…”

Section: Current Situations and Challengesmentioning

confidence: 99%

A New Reform of Mining Production and Management Modes under Industry 4.0: Cloud Mining Mode

Wang

et al. 2022

Applied Sciences

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In the context of Industry 4.0, using a new generation of information technology to activate and transform traditional industries will maintain the long-term competitiveness of traditional industries. The mining industry is also going through the process of informatization transformation. Through a literature survey, we analyze the current situation and challenges faced by mine production and operation management. Many mining companies are expanding in scale, but their operation and management methods are inefficient, and their business processes and organizational management methods need to be reformed. We propose a new mode named CM mode (cloud mining mode). We define this as integrating the core business of the mine (such as production and operation management, mining technology, planning services, etc.) into the cloud through effective use of cloud technologies, cloud resources, and cloud services. A large number of human and intellectual resources move to the cloud. A new mode of operation and management of mining industry clusters is thus formed; it is open, cooperative, and coordinated. We present five elements of the CM mode: data resources, digital technologies, digital talents, cloud business form, and cloud cooperation mode. We establish a “cloud–edge–terminal” technical framework of the CM mode, and describe its technical characteristics. We also describe three main application scenarios of the CM mode, and highlight the development path and key points of construction. The CM mode highlights a new development direction for the production and management of intelligent mines, and is of great significance for giving full play to the value of intelligent construction.

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“…Build a data mining library. After having a preliminary understanding of the original database, collect and organize effective data information [18]; then describe it, perform data quality assessment and data cleaning, and finally integrate and construct metadata to establish its own data mining library, and continue to load and maintain data mining library [19,20].…”

Section: Steps Of Data Miningmentioning

confidence: 99%

Data Mining Technology in Book Copyright Information Management Decision System

Song

2021

Mobile Information Systems

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Today is an era of data “big bang”; Internet information technology is widely used in various fields of society. As an indispensable spiritual food in people’s daily life, books are increasing in number and scale. In order to better manage book information, people have introduced data mining technology. Based on this, this article takes the research and application of data mining technology in book copyright information management decision-making system as the theme, explores the role of data mining technology in book copyright information management, and aims to provide reference for our country’s book copyright information management and decision-making. This article first introduces the common algorithms of data mining technology and then elaborates on the advantages and effectiveness of the association rule method in data mining. Aiming at some defects of the original Apriori algorithm of the association rule method, an improved Apriori algorithm is proposed. After taking the library book information management system and database of a university in our province as the experimental research object, the performance gap between the two algorithms is compared through experiments, and it is concluded that when the number of transaction set item records is less than 1400, the Apriori algorithm performs better, and when the number of records in the transaction set is greater than 1400, the improved Apriori algorithm is obviously more advantageous. The research results show that the introduction and application of data mining technology make the information management of books more efficient and convenient, and it is more convenient for the management and decision-making of book copyright information.

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A Mining Technology Collaboration Platform Theory and Its Product Development and Application to Support China’s Digital Mine Construction

Cited by 18 publications

References 30 publications

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

A New Reform of Mining Production and Management Modes under Industry 4.0: Cloud Mining Mode

Data Mining Technology in Book Copyright Information Management Decision System

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