State Of Art Approach For Prediction Of Gross Calorific Value Of Coal Using Machine Learning Algorithm Mustafa Acikkar et al. [10] show how to use support vector machines (SVMs) and a feature selection approach to create new GCV, prediction models. To identify the relevance of each GCV predictor, the feature selector RReliefF is used to a ...
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— This paper presents the application of three regression models, i.e., support vector machine (SVM), alternating conditional expectation (ACE) and back propagation …
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— Based on research of the relationship between the industrial analysis of coal composition and the calorific value, a multiple linear regression - support vector machine model for predicting calorific value of coal is put forward. The training sample set is made up of the original industrial analysis data and calorific value. Then the preliminary predicted …
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— In this paper, a coal calorific value detection technique based on NIRS-XRF fusion spectroscopy was proposed, which used NIRS to detect organic functional groups …
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Rapid determination of the gross calorific value of coal using laser-induced breakdown spectroscopy coupled with artificial neural networks and genetic algorithm.
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— 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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Hardgrove Grindability Tester measures the relative ease of pulverization of coal compared to standard coal samples in accordance with ASTM D409 Hardgrove Machine Method. The resulting Hardgrove Grindability Index (HGI) provides a measure of the energy required in a grinding process or a measure of yield for given energy input.
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Keywords: coal, RBFNN, GCV, GRNN, Machine learning, ML, SVM. I. INTRODUCTION Coal is the most abundant and commonly used fossil fuel on the planet. It is a global industry that contributes significantly to global economic growth. Coal is mined commercially in more than 50 nations and used in more than 70. Annual global coal usage is
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— Maixi Lu, Zhou C (2009) Coal calorific value prediction with linear regression and artificial neural network. Coal Sci Technol 37:117–120. Google Scholar ... Support vector machine regression—an alternative to neural networks (ANN) for analytical chemistry. Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. ...
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Downloadable (with restrictions)! Measuring the heating value through experimentation is a laborious process that demands precise instruments and a skilled technician. Due to the challenges associated with experimental determination of calorific value, a wide range of linear and non-linear models have been created as an alternative approach.
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DOI: 10.1016/J.FUEL.2016.03.031 Corpus ID: 101676694; Estimation of coal gross calorific value based on various analyses by random forest method @article{Matin2016EstimationOC, title={Estimation of coal gross calorific value based on various analyses by random forest method}, author={S. S. Matin and Saeed Chehreh …
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— The identification technology for coal and coal-measure rock is required across multiple stages of coal exploration, mining, separation, and tailings management. However, the construction of ...
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— Proximate analysis, including ash, volatile matter, moisture, fixed carbon, and calorific value, is a fundamental aspect of fuel testing and serves as the primary method for evaluating coal quality, which is critical for the processing and utilization of coal. The traditional analytical methods involve time-consuming and costly combustion processes, …
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Coal gcv testing machine, automation grade: digital, model n... Digital 2kva coal testing equipments, packaging type: box, m... Coal testing equipments; ... To check Calorific Value of Coal. Heat Capacity: 14000- 15000J/K. Display Type: LCD. read more... Brochure. Redius Solutions.
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— Coal is the primary energy source in China, widely used in energy production, industrial processes, and chemical engineering. Due to the complexity and diversity of coal quality, there is an urgent need for new technologies to achieve rapid and accurate detection and analysis of coal, aiming to improve coal resource utilization and reduce …
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— Calorific value testing machine using bomb calorimeter test method, can be used to measure the calorific value of solid or liquid samples, including coal, petroleum, ecology, energy metabolism in animal nutrition studies, physical, the chemical conclusion, etc. ... ASTM D240 Calorific Value Testing Machine for Petroleum Coal Oil. Posted on ...
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— The calorific value (CV) as an indicator of the chemically stored energy in coal is a very important parameter in the assessment of its value as a fuel [4], [5], and potentially could be a basis for the purchase of coal [6]. CV (heating value) is the amount of energy per unit mass released upon complete combustion [7].
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— Such attributes have direct relevance to the complex systems modelled in the coal industry [e.g., gas calorific value (GCV) prediction and coal petrology–grindability relationships]. ... Other machine learning algorithms and empirical relationships that are underpinned by correlations cannot easily deliver this level of detail into the degree ...
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Calorific value is an essential fuel parameter during the process of energy utilization. Forty-four coal samples with different calorific values were quantitatively analyzed by laser-induced breakdown spectroscopy (LIBS) in this paper. The influences of different spectral preprocessing methods such as smoothing, standard normal variate transformation …
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DOI: 10.1016/J.FUEL.2017.03.012 Corpus ID: 99746104; Prediction models of calorific value of coal based on wavelet neural networks @article{Wen2017PredictionMO, title={Prediction models of calorific value of coal based on wavelet neural networks}, author={Xiao Qiang Wen and Shuguang Jian and Jianguo Wang}, journal={Fuel}, …
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— Least squares support vector machine (LSSVM) is a variation of the classical SVM, which has minimal computational complexity and fast calculation. This paper …
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— DOI: 10.1080/19392699.2024.2339340 Corpus ID: 269153347; Estimation of gross calorific value of coal: A literature review @article{Vilakazi2024EstimationOG, title={Estimation of gross calorific value of coal: A literature review}, author={Lethukuthula N. Vilakazi and Daniel Madyira}, journal={International Journal of Coal Preparation and …
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— Coal, as it is commonly known, is a solid fossil hydrocarbon fuel material. The gross calorific value of coal is frequently used when determining the total calorific value for a specific amount of coal for fuel …
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— Gross calorific value (GCV) of coal was predicted by using as-received basis proximate analysis data. Two main objectives of the study were to develop prediction models for GCV using proximate ...
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— Introduction. Fossil fuels including fuel oil, natural gas, and coal mostly meet the world's energy needs (Hagen and Robinson Citation 2002).With regards to fossil fuels, coal is the most plentiful energy source, accounting for 40% of global energy (Mathews et al. Citation 2009).Coal provides 77% of South Africa's energy needs, 95% of this energy …
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— As one of the most important indicators of coal, calorific value (CV) not only determines the value of coal product, but also has a significant impact on the further …
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DOI: 10.1016/j.energy.2023.127666 Corpus ID: 258361035; Calorific value prediction of coal and its optimization by machine learning based on limited samples in a wide range @article{Bykkanber2023CalorificVP, title={Calorific value prediction of coal and its optimization by machine learning based on limited samples in a wide range}, …
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Accurately detecting these two indicators is of great significance for carbon accounting. In this study, we developed a compact coal quality rapid detection integrated machine …
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— 1. Introduction. Over the years, there has been an increasing demand for sustainable and renewable sources of energy. Energy production and energy utilization symbolize the economic progress of a country [1].Regarding energy production through renewable sources, India ranks third among the countries in the world [2].Global …
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— There are also studies using the RF method to predict the calorific value. These studies focused on the calorific value prediction of producer gas from biomass gasification [1], pyrolytic bio-oil from fast pyrolysis of biomass [4], municipal solid waste [13], biomass-biochar-hard coal [24], torrefied biomass [25], coal [26].
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— Coal is the world's most abundant and widely used primary energy source. ... Prediction of gross calorific value as a function of proximate parameters for Jharia and Raniganj coal using machine learning based regression methods ... This study aims to investigate the relation between Gross calorific value (GCV) and coal proximate …
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— In this study, the gross calorific value (GCV) of coal was accurately and rapidly determined using eight artificial intelligence models based on big data of 2583 …
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— 1. Introduction. Coal is an incredibly heterogeneous natural material encountered on Earth. It may involve up to 76 of the 98 naturally developing chemical components, most appearing as traces [].Assessments, such as calorific value, ultimate analysis, and proximate analysis determine the energy quality of coal.
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