Search scope:
排序: Display mode:
Using Text Mining to Evaluate the China Manufacturing Regional Action Plan
Kong Dejing Dong Fang Li Zhaofu Qu Xianming
Strategic Study of CAE 2017, Volume 19, Issue 3, Pages 149-158 doi: 10.15302/J-SSCAE-2017.03.021
Guidelines for the implementation of the China Manufacturing Regionaldocuments based on Chinese word segmentation, feature extraction, and similarity calculation using textmining, which can help to analyze a large number of policy documents efficiently.
Keywords: regional action plan text mining similarity calculation
The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data
Yang Bingru,Tang Qing
Strategic Study of CAE 2003, Volume 5, Issue 1, Pages 56-61
This paper discusses the macroscopic and important problem in the field of KDD. First, it is very difficult to describe the complex type data by general knowledge representation method. So the authors use pattern, which is defined as the vector in Hilbert Space, to represent the characteristic of complex type data. It also can be used to describe the rule of knowledge discovery. Second, the general structure model is constructed based on complex type data—DFSSM (discovery feature sub-space model ) following by the research on inner mechanism of knowledge discovery system. At last, the authors prove the practicability and validity of this general structure model i. e. DFSSM which can guide the knowledge discovery of textual data and image data (meteorological echogram data). It will beapplied in other complex type data in future.
Keywords: complex type data data mining text mining
Intelligent Petroleum Engineering Perspective
Mohammad Ali Mirza, Mahtab Ghoroori, Zhangxin Chen
Engineering 2022, Volume 18, Issue 11, Pages 27-32 doi: 10.1016/j.eng.2022.06.009
Data-driven approaches and AI algorithms are promising enough to be relied on even more than physics-based methods; their main feed is data which is the fundamental element of each phenomenon. These algorithms learn from data and unveil unseen patterns out of it. The petroleum industry as a realm where huge volumes of data are generated every second is of great interest to this new technology. As the oil and gas industry is in the transition phase to oilfield digitization, there has been an increased drive to integrate data-driven modeling and machine learning algorithms in different petroleum engineering challenges. ML has been widely used in different areas of the industry. Many extensive studies have been devoted to exploring AI applicability in various disciplines of this industry; however, lack of two main features is noticeable. Most of the research is either not practical enough to be applicable in real-field challenges or limited to a specific problem and not generalizable. Attention must be given to data itself and the way it is classified and stored. Although there are sheer volumes of data coming from different disciplines, they reside in departmental silos and are not accessible by consumers. In order to derive as much insight as possible out of data, the data needs to be stored in a centralized repository from where the data can be readily consumed by different applications.
Keywords: Artificial intelligence Machine learning Intelligent reservoir engineering Text mining Intelligent
Topicmodeling for large-scale text data
Xi-ming LI,Ji-hong OUYANG
Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6, Pages 457-465 doi: 10.1631/FITEE.1400352
Keywords: Latent Dirichlet allocation (LDA) Topic modeling Online learning Moving average
A new feature selection method for handling redundant information in text classification None
You-wei WANG, Li-zhou FENG
Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2, Pages 221-234 doi: 10.1631/FITEE.1601761
Keywords: Feature selection Dimensionality reduction Text classification Redundant features Support vector machine
Frontiers in Personless Mining and Avenues of Their Advancement in China
Li Zhongxue,Li Cuiping,Liu Shuangyue
Strategic Study of CAE 2007, Volume 9, Issue 11, Pages 16-20
With the rapid social and economic development in China, technologydepth and other adverse conditions confronted by the mining industries, increase the efficiencyof extracting mineral resources, and safeguard the safety and health of mining workers.to enhance technology innovations in personless mining and provide the mining industries with a freshperspective to personless mining.
Keywords: hard-rock mining automated mining personless mining personless mine
The Research of Mining the Mutative Knowledge With Extension Data Mining
Chen Wenwei
Strategic Study of CAE 2006, Volume 8, Issue 11, Pages 70-73
Keywords: extension information extension knowledge extension data mining extension reasoning
Recent Science and Technology Frontier for Exploitation of Underground Metal Resources
Yu Runcang
Strategic Study of CAE 2002, Volume 4, Issue 9, Pages 8-11
With the development of rockmechanics, extensive application of computer in mining area and promotionby intersection of multi-course, mining starts entering the science field, being regarded as skill alwaysand technology at the frontier for exploitation of underground metal resources: digital control of miningenvironment, wasteless mining, ocean mining and coping with threat of rockburst in deep mining, thatare of great importance to the development of mining course.
Keywords: mining metal resource digital control of mining environment wasteless mining
Da-zhao Gu
Frontiers of Engineering Management 2016, Volume 3, Issue 1, Pages 59-66 doi: 10.15302/J-FEM-2016010
Keywords: Western Mining Area coal mining water resources coal mine underground reservoirs
Driving Factors of Green Mining in Coal Mining Enterprises in China
Lin-xiu Wang,Mu-xi Yu,Si-jia Wang
Frontiers of Engineering Management 2015, Volume 2, Issue 3, Pages 211-223 doi: 10.15302/J-FEM-2015043
Keywords: Green Mining driving factor Structural Equation Model empirical study
Energy and Mining Engineering Front 2019
Energy and Mining Engineering Project Team
Engineering Fronts 2019, Volume 3, Issue 1, Pages 73-102
Energy and Mining Engineering Front 2022
Energy and Mining Engineering Project Team
Engineering Fronts 2022, Volume 6, Issue 1, Pages 92-123
Digital Mine Research and Practice Based on Mining and Metallurgy System Engineering
An-lin Shao
Frontiers of Engineering Management 2016, Volume 3, Issue 1, Pages 67-73 doi: 10.15302/J-FEM-2016006
Keywords: exploration of lean iron ore mining and metallurgy system engineering digital mine wisdom mine
Anlin SHAO
Frontiers of Engineering Management 2017, Volume 4, Issue 3, Pages 375-378 doi: 10.15302/J-FEM-2017108
Title Author Date Type Operation
Using Text Mining to Evaluate the China Manufacturing Regional Action Plan
Kong Dejing Dong Fang Li Zhaofu Qu Xianming
Journal Article
The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data
Yang Bingru,Tang Qing
Journal Article
Intelligent Petroleum Engineering
Mohammad Ali Mirza, Mahtab Ghoroori, Zhangxin Chen
Journal Article
Yang Chengqi: Research on Big Data of Energy and Environmental Protection Policies Based on Text Mining
19 May 2022
Conference Videos
A new feature selection method for handling redundant information in text classification
You-wei WANG, Li-zhou FENG
Journal Article
Frontiers in Personless Mining and Avenues of Their Advancement in China
Li Zhongxue,Li Cuiping,Liu Shuangyue
Journal Article
The Research of Mining the Mutative Knowledge With Extension Data Mining
Chen Wenwei
Journal Article
Recent Science and Technology Frontier for Exploitation of Underground Metal Resources
Yu Runcang
Journal Article
Technology Development and Engineering Practice for Protection and Utilization of Water Resources in Coal Mining
Da-zhao Gu
Journal Article
Driving Factors of Green Mining in Coal Mining Enterprises in China
Lin-xiu Wang,Mu-xi Yu,Si-jia Wang
Journal Article
Digital Mine Research and Practice Based on Mining and Metallurgy System Engineering
An-lin Shao
Journal Article