WEBApr 1, 2017 · The thickness of tectonically deformed coal (TDC) has positive correlation associations with gas outbursts. In order to predict the TDC thickness of coal beds, we propose a new quantitative predicting method using an extreme learning machine (ELM) algorithm, a principal component analysis (PCA) algorithm, and seismic attributes.
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WEBNov 1, 2021 · In this study, we developed an automatic Ppick quality control model based on machine learning to identify useable/unusable Ppicks. ... Pd, and As in bulk metallurgical or coalbased solid waste greatly surpasses the standard levels. Nevertheless, by mixing such waste within the coal mine backfill materials, the resulting .
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WEBDOI: / Corpus ID: ; Coal structure identifiion based on geophysical logging data: Insights from Wavelet Transform (WT) and Particle Swarm Optimization Support Vector Machine (PSOSVM) algorithms
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WEBJul 1, 2022 · Abstract. In this paper, YOLOv4 algorithm based on deep learning is used to detect coal gangue. Firstly, the data set of coal gangue was made, which provides sufficient data for the training and verifiion of the detection algorithm model. Then, the coal gangue data set was used to test the influence of the combined use of optimization ...
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WEBDec 5, 2022 · Professor Shan Pengfei adopted a coalrock identifiion method based on machine deep learning FasterRCNN, which realized the accurate identifiion and loion of coal seam and rock stratum ...
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WEBSep 1, 2023 · Effects of Nibased composite coatings on failure mechanism and wear resistance of cutting picks on coal shearer machine. ... After completing the field studies in a real scale coal cutting machine and measuring the wear rate of the coated and uncoated picks refer to cutting operation length, the results of these measurements were analyzed .
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WEBMine work face gas emission quantity is an important mine design basis, which also has important practical significance for guide mine design, ventilation and safety production. Mine gas emission quantity and work face multi factors have complex nonlinear relationship. The paper built the work face gas emission prediction support vector .
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WEBJan 1, 2007 · The support vector machines (SVM) model with multiinput and single output was proposed. Compared the predictor based on RBF neural networks with test datasets, the results show that the SVM ...
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WEBBecause of its complex working environment, most coal mines take belt conveyor as the main transportation equipment. However, in the process of transportation, due to longtime and highintensity operation, the belt is very easy to be damaged by gangue, iron and other foreign matters doped in coal, resulting in unnecessary losses. Foreign objects in the .
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WEBDec 15, 2021 · The subclass level classifiion also obtained good results with an accuracy of and F1 score of The results demonstrate the effectiveness of rapid coal classifiion systems based on DRS dataset in combination with different machine learningbased classifiion algorithms.
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WEBAbstract. Read online. The classifiion of surrounding rock stability of coal roadway has important theoretical and practical significance for the design, construction and management of onsite rock mass paper selected seven key indexes that affect the surrounding rock stability of coal roadway, collected the samples through field .
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WEBNov 20, 2022 · Based on differences in coal rock texture features, Meng and Li put forward a GLCM and BPNNbased coal rock interface identifiion method. Wu and Tian ; Wu, Zhang proposed a ... Deep learning is a machine learning method based on a deep network model. To be specific, inspired by the concept of "receptive field" in the .
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WEBApr 12, 2022 · Machine learning prediction of calorific value of coal based on the hybrid analysis. April 2022. International Journal of Coal Preparation and Utilization 43 (1):122. DOI: / ...
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WEBMay 1, 2013 · A neural network prediction method based on an improved SMOTE algorithm expanding a small sample dataset and optimizing a deep confidence network was proposed, which can be used to better predict and analyze coal mine water inrush accidents, improve the accuracy of water in rush accident prediction, and encourage the .
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WEBMar 15, 2024 · The life cycle inventory of coal power generation in China was obtained from the CPLCID® (Chinese processbased life cycle inventory database, Zhang et al., 2016), which primarily includes an internationally peerreviewed inventory of subcritical, supercritical, and ultrasupercritical technologies for coal power generation (Hong et al., .
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WEBMar 10, 2017 · Gross calorific value (GCV) is one the most important coal combustion parameters for power plants. Modeling of GCV based on coal properties could be a key for estimating the amount of coal consumption in the combustion system of various plants. In this study, support vector regression (SVR) as a powerful prediction method has been .
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WEBA coal mine mantrip at Lackawanna Coal Mine in Scranton, Pennsylvania Coal miners exiting a winder cage at a mine near Richlands, Virginia in 1974 Surface coal mining in Wyoming, A coal mine in Frameries, Belgium. Coal mining is the process of extracting coal from the ground or from a mine. Coal is valued for its energy content and .
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WEBJun 1, 2019 · Wang et al. [13] constructed a classifiion model of coal based on a confidence machine, a support vector machine algorithm and nearinfrared spectroscopy, and a good classifiion result was obtained. Gomez et al. [14] used Fourier transform infrared photoacoustic spectroscopy combined with partial least squares to predict ash .
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WEBJan 13, 2022 · Since hundreds or thousands of patches can be extracted from each image, the patch database is much larger than the rock and coal image database. The machine learning process is based on the patches. As discussed earlier, the RGB images are stored as threedimensional arrays, and the extraction of patches is accomplished by extracting .
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WEBThis paper presents a novel coal mill modeling technique using genetic algorithms (GA) based on routine operation data measured onsite at a National Power (NP) power station, in England, The work focuses on the modeling of an Etype vertical spindle coal mill. The model performances for two different mills are evaluated, covering a whole range of .
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WEBJan 1, 2023 · The DNN memorybased models show significant superiority over other stateoftheart machine learning models for short, medium and long range predictions. The transformerbased model with attention enhances the selection of historical data for multihorizon forecasting, and also allows to interpret the significance of internal power plant ...
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WEBSep 1, 2018 · A coal proximate analysis method based on a combination of visibleinfrared spectroscopy and deep neural networks. This method can fate examines the moisture, ash, volatile matter, fixed carbon, sulphur and low heating value in coal. Compared with traditional coal analysis, this method has unparalleled advantages and .
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WEBSep 1, 2021 · Among them, the sensorbased equipment is a hightech classifiion method with high efficiency, low cost, and no pollution, so it has the potential for mineral preenrichment and presorting in industrial appliions. At present, sensorbased ore sorting technology is mainly divided into two types: ray sensorbased and machine .
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WEBJul 26, 2018 · Third, we proposed a multilayer extreme learning machine algorithm and constructed a coal classifiion model based on that algorithm and the spectral data. The model can assist in the classifiion of bituminous coal, lignite, and noncoal objects.
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WEBJun 1, 2022 · Accordingly, eigenvectors of coal and rock images are computed based on thermal imaging cloud images from coal and rock cutting trials. The traditional recognition technology of coal and rock mainly adjusts the height of the drum of the coal winning machine by manually observing the state of coal and rock and listening to the sound.
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WEBBituminous coal is the most abundant rank of coal found in the United States, and it accounted for about 46% of total coal production in 2022. Bituminous coal is used to generate electricity and is an important fuel and raw material for making coking coal for the iron and steel industry. Bituminous coal was produced in at least 16 states ...
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WEBDec 3, 2021 · Based on the above, this scheme designs the mine belt conveyor deviation fault detection system based on machine vision, uses mine camera to collect images, uses OpenCV visual library compiler software for image processing, carries on the clear processing to the coal mine image, effectively reduces the coal dust influence, .
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WEBApr 26, 2023 · The problem of dust pollution in the openpit coal mine significantly impacts the health of staff, the regular operation of mining work, and the surrounding environment. At the same time, the openpit road is the largest dust source. Therefore, it analyzes the influencing factors of road dust concentration in the openpit coal mine. It is of practical .
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WEBOct 22, 2023 · The belt conveyor is a key piece of equipment for thermal power plants. Belt mistracking causes higher economic costs, lower production efficiency, and more safety accidents. The existing belt correction devices suffer from poor performance and high costs. Therefore, a design method for coal conveying belt correction devices is proposed in .
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WEBThe paper analyzed coal mine safety investment influence factors and established coal mine safety investment prediction model based on support vector machine. Finally, the paper adopted survey data of a mine in Huainan to exemplify and compare with traditional BP network, which proved the method feasibility and effectivity.
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WEBAug 1, 2021 · IoTenabled sensor devices and machine learning methods have played an essential role in monitoring and forecasting mine hazards. In this paper, a prediction model has been proposed for improving the safety and productivity of underground coal mines using a hybrid CNNLSTM model and IoTenabled sensors. The hybrid CNNLSTM .
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A material supplier from Belgium would like to produce limestone powder for his custome...
India is rich in various mineral resources and it is an important mineral processing market
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