Results 1 to 10 of about 9,993 (95)

Coal gangue recognition based on spectral imaging combined with XGBoost

open access: yesPLoS ONE, 2023
The identification of coal gangue is of great significance for its intelligent separation. To overcome the interference of visible light, we propose coal gangue recognition based on multispectral imaging and Extreme Gradient Boosting (XGBoost).
Minghao Zhou, Wenhao Lai
semanticscholar   +1 more source

Coal-gangue recognition via multi-branch convolutional neural network based on MFCC in noisy environment

open access: yesScientific Reports, 2023
Traditional coal-gangue recognition methods usually do not consider the impact of equipment noise, which severely limits its adaptability and recognition accuracy.
Haiyan Jiang   +6 more
semanticscholar   +1 more source

Research on Coal Gangue Recognition Based on Multi-source Time–Frequency Domain Feature Fusion

open access: yesACS Omega, 2023
The over-exploitation of resources caused by the increasing coal demand has resulted in a sharp increase in solid waste emissions mainly gangue, which has made the burden on the environment, economy, resources, and society of our country heavier.
Y. Zhang, Yang Yang, Qingliang Zeng
semanticscholar   +1 more source

Research on the Strong Generalization of Coal Gangue Recognition Technology Based on the Image and Convolutional Neural Network under Complex Conditions

open access: yesACS Omega, 2023
A coal gangue image recognition method based on complex conditions is proposed to address the current issue of image-based coal gangue recognition being greatly affected by complex conditions.
Qikai Xun, Yang Yang, Yongbin Liu
semanticscholar   +1 more source

Spectral Estimation Model Construction of Heavy Metals in Mining Reclamation Areas [PDF]

open access: yes, 2016
The study reported here examined, as the research subject, surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR ...
Dai, W, Dong, J, Li, S, Xu, J
core   +3 more sources

Coal Gangue Recognition during Coal Preparation Using an Adaptive Boosting Algorithm

open access: yesMinerals, 2023
: The recognition of coal and gangue is the premise and foundation of coal gangue intelligent sorting. Adaptive boosting (AdaBoost) algorithm-based coal gangue identification has not been studied in depth.
G. Xue   +5 more
semanticscholar   +1 more source

Performance Analysis of Coal Gangue Recognition Based on Hierarchical Filtering and Coupled Wrapper Feature Selection Method

open access: yesIEEE Access, 2023
Coal gangue recognition of top coal caving is one of the important links in the process of intelligent coal mine construction. However, the recognition accuracy of this technology in practical application is still challenging, because the recognition ...
He Li   +3 more
semanticscholar   +1 more source

Discrete X-ray tomographic reconstruction for fast mineral liberation spectrum retrieval [PDF]

open access: yes, 2015
In minerals beneficiation, the mineral liberation spectrum of the plant feed conveys valuable information for adjusting operations, provided it is available in minutes from particulate sampling.
Piller, Marzio   +2 more
core   +1 more source

Research and application of key technology of intelligent coal caving in high gas fully-mechanized top coal caving face [PDF]

open access: yes, 2023
At present, intelligent coal caving in high gas fully mechanized top coal caving face is facing many problems, mainly including poor recognition accuracy of coal gangue, incomplete control research on coal flow and gas concentration, cumbersome design ...
Jinghong WU   +3 more
core   +1 more source

Plate tectonic aspects of the Triassic carbonate-hosted stratiform-stratabound base-metal deposits in the Western Balkan, NW Bulgaria [PDF]

open access: yes, 2016
The Triassic carbonate-hosted stratiform-stratabound base-metal deposits in the Western Balkan, NW Bulgaria, have well defined regional geological and tectonic settings, style ofmineralisation, mineralogical, geochemical and isotopic data. Their genesis,
Irina Marinova, Zhelyazko Damyanov
core   +2 more sources

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