Technological advances and trends in the mining industry: a …
This paper aims to identify the most used technologies in the mining industry, determine in which mining processes these technologies are applied, assess their positive …
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A novel behavioral model of the pasture-based dairy cow
Search ScienceDirect. Journal of Dairy Science. Volume 99, Issue 3, March 2016, Pages 2063-2075. A novel behavioral model of the pasture-based dairy cow from GPS data using data mining and machine learning techniques. Author links open overlay panel M.L. Williams *, ...
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Artificial Intelligence in Future Mining | ScienceDirect
Machine-learning-based modeling plays a key role in tackling the complexities of urban mining, enabling the development of predictive models for efficient postconsumption product and …
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Alternative data mining/machine learning methods for
Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity – A review Author links open overlay panel Ana M. Jiménez-Carvelo, Antonio González-Casado, M. Gracia Bagur-González, Luis Cuadros-Rodríguez
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Machine learning for prediction of 30-day mortality
Prediction of allogeneic hematopoietic stem-cell transplantation mortality 100 days after transplantation using a machine learning algorithm: a European Group for Blood and Marrow Transplantation Acute Leukemia Working Party retrospective data mining study
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Fracture failure analysis of internal teeth of ring
The ring gear is widely used in cutting reducer of coal mining machine for transmitting the cutting torque during the cut process. The ring gear of transmission system in the cutting reducer fractured and fell into pieces after 8 h of service in the trial run state.Emergency stop coal seam shearer was executed for maintenance and the results revealed fracture of …
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Exploring the impact of ChatGPT on education: A web mining and machine
mining was used to scour the internet for relevant articles and extract data for the study. This approach is widespread in scholarly works concentrating on text mining for web content (Singh & Singh, 2010). Conceptually, web mining represents the process of using data mining methods to extract useful information from the web.
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Software fault prediction using data mining, machine
Software fault/defect prediction assists software developers to identify faulty constructs, such as modules or classes, early in the software development life cycle.There are data mining, machine learning, and deep learning techniques used for software fault prediction. We perform analysis of previously published reviews, surveys, and related studies to distill a …
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Machine learning combined with geodetector to predict
Search ScienceDirect. Science of The Total Environment. Volume 959, 10 January 2025, 178281. Machine learning combined with geodetector to predict the spatial distribution of soil heavy metals in mining areas. Author links open overlay panel Haolong Hu a, ... Mining activities are one of the main sources of soil HM pollution, ...
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Landslide risk assessment in mining areas using hybrid machine …
The total area of high risk and very high risk in Tunlan mine was 4. 596 %, and the areas of high risk and very high risk in Xiqu mine, Zhenchengdi mine, and Baijiazhuang mine accounted for 3. 855 %, 3.625 %, and 3. 188 % respectively. Among them, the Xiqu mine had the largest area of extremely high risk, which accounted for 1.373 %.
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Data mining with 12 machine learning algorithms for
Search ScienceDirect. Energy Conversion and Management. Volume 238, 15 June 2021, 114153. Data mining with 12 machine learning algorithms for predict costs and carbon dioxide emission in integrated energy-water optimization model in buildings. Author links open overlay panel Majid Emami Javanmard a b, ...
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Preserving complex object-centric graph structures to improve machine …
On the other hand, an extensive amount of general machine learning methods based on graphs has been proposed. However, the graph-based structure of object-centric event data has, so far, been neglected in machine learning tasks in process mining. Machine learning has become a central pillar in providing operational support for processes.
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A spatial machine learning approach to exploring the
Since the coal mining areas accounted for only 3.6% of the total study area, a low contribution of coal mining to ecosystem health was observed. However, in coal mining areas, the mining intensity was the dominant contributing factor affecting EH (Fig. 5). The distance to the mining areas contributed about 10% to the EH during the study period.
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Data mining and machine learning in cancer survival
Search ScienceDirect. Journal of Biomedical Informatics. Volume 128, April 2022, 104026. ... (Prediction OR Prognosis), and techniques (Data mining OR Machine learning OR Classification OR Rule mining OR Sequence mining) were used on the title and abstract for the analysis from each of the databases. A total of 1378 publications were retrieved ...
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Perceived usefulness of online customer reviews: A review mining …
It has been defined by researchers as one of the key data mining techniques. Standard data mining techniques are used to extract logical patterns from structured data, while text mining is a process of knowledge discovery and a technique for identifying logical patterns from unstructured data (Kano et al., 2009).
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Applications of geographically weighted machine
Cd often occurs as a byproduct of Zn ore mining and refining, with levels typically elevated in areas surrounding mining sites (Sadegh Safarzadeh et al., 2007). Pb is associated with various mining operations, including Pb, Zn, and Ag mining, and can persist in the environment for extended periods (Kumar et al., 2020).
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Optimization of collection efficiency for a dual-row jet …
In this work, we employ a coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) approach with the objective of enhancing the collection efficiency of deep …
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Recent advances in data mining and machine learning for
Previous studies have reviewed the applications of data mining (DM) or machine learning (ML) in building operations. For example, Zhao et al. [19] reviewed the application of DM techniques for BESs, including load prediction, pattern identification, and fault detection and diagnosis.Wang et al. [20] reviewed the use of reinforcement learning (RL) algorithms for …
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Development of a new method for maintainability …
Shovels are universally acknowledged as vital machinery in surface mining production systems, and enhancements to this equipment substantially augment operational mine output capacity.
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Digitization of the mining industry: Pathways to
Big data, AI, machine learning, autonomous vehicles enable sustainable mining and high production efficiency. Digitization addresses mining's environmental impact and …
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Development of a Hard Rock Continuous Mining Machine
Due to the priority exercised by MIM, the experience with this machine has rapidly evolved the Mobile Miner concept as a potentially viable mining system. It is not too difficult to …
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Data Mining and Machine Learning for Condition-based
© 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing. Keywords: condition-based maintenance; data analytics; data mining; machine learning; failure event * Corresponding author.
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Data mining and machine learning techniques applied to
Data mining and machine learning applications in public health. DM and ML have been extensively used to research health problems. Several studies have been carried out using a wide variety of tools. ... PubMed, ScienceDirect, Scopus and Web of Science databases. As for the predictive model for risk of readmission to hospitals, Artetxe ...
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Machine learning and data mining in manufacturing
Machine learning (ML) is an important research field of artificial intelligence that assists computers in modeling based on experiences and accurately predicting future events. The major ML approaches can be classified into two main categories: supervised learning (Parvin, Alinejad-Rokny, Minaei-Bidgoli, & Parvin, 2013) and unsupervised learning (Minaei-Bidgoli, …
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Exploring the factors that affect user experience in
Search ScienceDirect. Journal of Business Research. Volume 156, February 2023, 113484. ... Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application. Journal of Business Research, 131 (2021), pp. 815-825. View PDF View article View in Scopus Google Scholar.
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Injury severity on traffic crashes: A text mining …
This technique has been successfully used in various machine-learning-based text mining studies. For instance, Amrit et al. (2017) used text mining to analyze consultation notes from public health institutions to identify …
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Web Data Mining
Three Open Problems in the Context of E2E Web Testing and a Vision: NEONATE. Filippo Ricca, ... Andrea Stocco, in Advances in Computers, 2019. 3.1.1 Robust Data Extraction. In the context of information retrieval and web data mining, researchers have proposed techniques for the robust extraction of information from evolving structured documents (e.g., XML documents).
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Review of vibrating screen development trends: Linking
Search ScienceDirect. International Journal of Mineral Processing. Volume 145, 10 December 2015, Pages 17-22. ... Mining machinery industry transformation is oriented towards highly sophisticated technologies aimed at enhancing the nature of operations carried out. Vibrating screen machine is a major player in the mining processing plants and ...
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Data Science with Data Mining and Machine Learning A
With Data Science, Data Mining and Machine Learning platforms allow the development of decision support systems, capable of establishing patterns between data and …
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Integrating robotic systems in underground roof support machine
Search ScienceDirect. Journal of Industrial Safety. Volume 1, Issue 1, June 2024, 100002. Integrating robotic systems in underground roof support machine. ... Automated mining machines are designed according to their intended applications and are influenced by their specific operating and working conditions. The systems used in underground coal ...
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