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 ( P a ) to ...
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1. Introduction. Metal, as a limited natural resource, is an essential material for global economic development (Sykes et al., 2016).For example, Al and Fe have been widely used in building construction and machinery manufacturing (Soo et al., 2019), V is an important metallic material used in the production of ferrous and nonferrous alloys (Gao et al., 2020), and Cr has been used in ...
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Coal Mine Safety Evaluation Based on Machine Learning: A BP Neural Network Model As the core of artificial intelligence, machine learning has strong application advantages in multicriteria intelligent evaluation and decisionmaking. The level of sustainable development is of great significance to the safety evaluation of coal mining enterprises.
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article{osti_, title = {Development of novel dynamic machine learningbased optimization of a coalfired power plant}, author = {Blackburn, Landen D. and Tuttle, Jacob F. and Andersson, Klas and Fry, Andrew and Powell, Kody M.}, abstractNote = {The increasing fraction of intermittent renewable energy in the electrical grid is resulting in coalfired boilers now routinely ramp up and down.
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Professor Shan Pengfei adopted a coalrock identification method based on machine deep learning FasterRCNN, which realized the accurate identification and location of coal seam and rock stratum ...
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Abstract. The calorific value of coal is important in both the direct use and conversion into other fuel forms of coals. Accurate calorific value predicting is essential in ensuring the economic, efficient, and safe operation of thermal power plants. Least squares support vector machine (LSSVM) is a variation of the classical SVM, which has ...
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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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Highperformance and costeffective GPUbased instances for AI, HPC, and graphics workloads To power the development, training, and inference of the largest large language models (LLMs), EC2 P5e instances will feature NVIDIA's latest H200 GPUs, which offer 141 GBs of HBM3e GPU memory, which is times larger and times faster than H100 GPUs.
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Therefore, based on the analysis of humanmachine interaction in intelligent coal mine hoisting machine room, considering the applicability of SRK model and the understanding of IDA model on the ...
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Accumulators give off a circuit network signal. You can wire them to a power switch to isolate your steam engines as long as demand is being met elsewhere. If the accumulator falls below a threshold, toggle the engines back on. Look up how to make an SR latch (aka a memory toggle) with combinators.
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Longwall Miner. Twenty percent to 30 percent of mined coal underground is from longwall mining. This is performed by a mechanical cutter that shears coal off from a panel on the seam. The panel being worked on may be up to 800 feet in width and 7,000 feet in length. Mined coal is deposited onto a conveyor that moves the coal to a collection area.
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Chemical analysisbased, imagebased, and machinelearningbased methods are widely used for coal identification. The chemical analysisbased method is reliable and relatively accurate. However, this method requires stringent analysis techniques for elemental content, and it is easily affected by foreign chemical substances.
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A novel approach based on binocular machine vision and genetic algorithmbackpropagation neural network (GABPNN) was proposed. First, the sample image was segmented, and each region was judged to be coal or gangue. ... Prediction of density and sulfur content level of highsulfur coal based on image processing. Powder Technol., 407 (2022), p ...
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Get Price Quote. Voltage : 220V Capacity : 3000 Kgs to 3900 Kg per hour Weight : kg Power Consumption : 1 Hp to 30 Automatic Grade : Automatic used in chemicals, lime stone. bricks industries to make the coal briquettes for firing in furnaces and boilers. by this machine coal briquettes can be made in many shapes designs from coal dust powder with binding material. also used to ...
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Abstract. The higher heating value (HHV) of 84 coal samples including hard coals, lignites, and anthracites from Russia, Colombia, South Africa, Turkey, and Ukrania was predicted by multilinear regression (MLR) method based on proximate and ultimate analysis data. The prediction accuracy of the correlation equations was tested by Analysis of variance method. The significance of the predictive ...
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This paper presents an exploratory study employing a benchscale approach to detect the multiinformation of coal quality online by machine vision simultaneously, including particle size distribution, density distribution, the ash content of each density fraction, and the total ash content.
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The CIM is a joint product of the Massachusetts Institute of Technology and the Rhodium Group that catalogs and maps clean energy investments before and after the IRA passed. This work reflects an update and extension to our initial placebased analysis in The Inflation Reduction Act and Business Investment (August 2023). We offer two ...
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Coal is heterogeneous in nature, and thus the characterization of coal is essential before its use for a specific purpose. Thus, the current study aims to develop a machine vision system for automated coal characterizations. The model was calibrated using 80 image samples that are captured for different coal samples in different angles. All the images were captured in RGB color space and ...
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There exist many works where machine learning has been used for both simulated and physical optimization of combustion systems. Zheng et al. combine a support vector machine (SVM) with ant colony optimization (ACO) to optimize a 300 MW plant based on predicted NO x values (Zheng et al., 2008). Zheng et al. also compare the performance of ACO to ...
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efficiency. Both coal and gasbased DRI plants are operational in India. However, the share of coalbased DRI production is quite substantial and in comparison to gasbased production, this route is energy and carbonintensive. To meet the DRI production target of 80 million tonne by 203031 as envisaged under the
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The four elements (man, machine, environment, and management) in the coal mine and their synthesis are calculated and analyzed by using the Matlab tool and the BP neural network program. The predicted value of the personnel intrinsic safety value is (). The intrinsic safety value of the equipment is (, ).
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The machine learning models were optimized using hyperparameter tuning, and the most successful model was selected based on its regression and computational cost performance. Sensitivity analysis was conducted to investigate the performance of the coal properties on total desorbed gas content.
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This report presents the results of an exploratory machine learningbased analysis of green stormwater infrastructure asset data across five cities in the United States. Within each city, authors evaluated the location of installed green stormwater infrastructure based on the demographic and land use characteristics of the surrounding area.
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In our previous work, an approach based on image analysis and particle swarm optimizationsupport vector machine was presented (Wang et al. 2021) to detect the coalcarrying rate in gangue ...
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Coal is a black or brownishblack sedimentary rock that can be burned for fuel and used to generate is composed mostly of carbon and hydrocarbons, which contain energy that can be released through combustion (burning). Coal is the largest source of energy for generating electricity in the world, and the most abundant fossil fuel in the United States.
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Online estimation of ash content in coal based on machine vision has been paid more attention to by academia and industry. Existing research has mainly focused on feature extraction and model design for estimating ash content, but the exploration of the feature's contribution to the model is rarely reported.
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At present, coal gangue sorting technology based on machine learning is widely used . Liu C et al. established a comprehensive identification model of different ores and a support vector machine model through the texture characteristics of an image and completed the identification of different ores, thereby improving the efficiency of coal and ...
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Coal power plant cycling 1. Introduction The use of renewable energy sources (RESs) globally is projected to reach up to 30% by the end of 2030 [1]. In 2020, RES accounted for 21% of all the electricity generated in the United States [2]. The RESs, such as wind and solar, are considered as intermittent generating sources due to climatic conditions.
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CatBoost model. CatBoost is a new open source machine learning library proposed by Russian scholar Yandex in 2017, which is based on Categorical and Boosting (Prokhorenkova et al., 2018), a new gradient boosting algorithm that is implemented as a symmetric decision treebased ordered boosting, it improves the gradient estimation of the traditional Gradient Boosting Decision Tree ...
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Subsequently, a multiscale linear filter based on the Hessian matrix and Gaussian function was developed to obtain the edge intensity image. Finally, Experiment. The detection experiment of the coal content in gangue was carried out on the test rig shown in Fig. 10. The experimental samples were collected from the Hongliu coal preparation plant.
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India aims to add 17 gigawatts of coalbased power generation capacity in the next 16 months, its fastest pace in recent years, to avert outages due to a record rise in power demand, according to ...
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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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