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 1, 2021 · In this study, we developed an automatic Ppick quality control model based on machine learning to identify useable/unusable Ppicks. We used five waveform parameters, including signaltonoise ratio (SNR), signaltonoise variance ratio (SNVR), Pphase startingup slope ( K p ), shorttime zerocrossing rate (ZCR) and peak amplitude .
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WEBSpontaneous combustion of coal leading to mine fire is a major problem in most of the coal mining countries in the world. It causes major loss to the Indian economy. The liability of coal to spontaneous combustion varies from place to place and mainly depends on the coal intrinsic properties and oth .
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WEBJul 4, 2023 · Based on a particle swarm optimization algorithm and two machine learning algorithms, BP neural network and random forest, a prediction model of tar yield from oilrich coal is constructed in this ...
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WEBDec 1, 2014 · Xu et al. propose a coalrock interface recognition method during top coal caving based on Melfrequency cepstrum coefficient (MFCC) and neural network with sound sensor fixed on the tail beam of ...
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WEBSep 1, 2023 · With the trend of localization of imported coal machine reducers being imperative, the traditional reducer development method has the problems of a high failure rate in the design stage, a long development cycle, and high manufacturing costs. Based on reverse engineering, this paper discusses the process of localization and .
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WEBJun 3, 2021 · This paper uses this as a starting point to propose a distributed support vector machine model based on a cloud computing platform. The model is based on the existing popular MapReduce distributed computing framework, and completes the classifiion and prediction work in the coal system in a distributed manner. ... Environmental cost control ...
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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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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 1, 2013 · Maixi Lu, Zhou C (2009) Coal calorific value prediction with linear regression and artificial neural network. Coal Sci Technol 37:117–120. Google Scholar Jiang W, Hongqi W, Qu T (2011) Prediction of the calorific value for coal based on the SVM with parameters optimized by genetic algorithm. Thermal Power Gener 40:14–19
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WEBSep 1, 2023 · With the trend of localization of imported coal machine reducers being imperative, the traditional reducer development method has the problems of a high failure rate in the design stage, a long development cycle, and high manufacturing costs. ... Liu X 2020 Research on coal machine spare parts localization based on 3D measurement .
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WEBMar 23, 2022 · The technology of microseismic monitoring, the first step of which is event recognition, provides an effective method for giving early warning of dynamic disasters in coal mines, especially mining water hazards, while signals with a low signaltonoise ratio (SNR) usually cannot be recognized effectively by systematic methods. This paper .
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WEBDec 13, 2023 · The HTG diagrams are established based on previous work by Liu et al. 72 using coal as the investigated feedstock. HHV higher heating value, ER energy recovery, CR carbon recovery.
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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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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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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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WEBDec 8, 2023 · Liu et al. realized the approximate analysis of coal based on laserinduced breakdown spectra by combining principal component regression, artificial neural network, and PCAANN models. All of the above methods are used to deal with highdimensional spectral data using machine learning, but the direct use of machine learning algorithms .
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WEBDOI: / Corpus ID: ; Experimental analysis of vibratory screener efficiency based on density variation for screening coal and iron ore article{Shanmugam2023ExperimentalAO, title={Experimental analysis of vibratory screener efficiency based on density variation for screening coal and iron ore}, .
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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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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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WEBMay 27, 2021 · To detect the coalcarrying rate in gangue, a new method based on threedimensional (3D) image features and gray wolf optimizationsupport vector machine (GWOSVM) was proposed.
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WEBSep 1, 2023 · Based on reverse engineering, this paper discusses the process of localization and development of imported coal machine reducers and focuses on the five steps from the reducer design stage.
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WEBA coal mine mantrip at Lackawanna Coal Mine in Scranton, ... Technical and economic feasibility are evaluated based on the following: regional geological conditions; overburden characteristics; ... It is a sophistied machine with a rotating drum that moves mechanically back and forth across a wide coal seam. The loosened coal falls onto an ...
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WEBDec 21, 2021 · A coal gangue recognition method based on improved Support Vector Machine is proposed in this paper, and the experimental results show that the accuracy is %. In the process of coal mining, the separation of coal and gangue is a very important step. Traditional coal preparation methods include manual coal preparation, .
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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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WEBAug 25, 2021 · The appliion of machine learning techniques in coal mine gas concentration prediction and early warning can effectively prevent gas explosion accidents. Nearly all traditional prediction models use a regression technique .
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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.
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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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