— 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 …
— Recently, we have successfully developed a rapid coal calorific value analyzer based on NIRS-XRF technology [21], which has been applied in a certain coal washing plant. For the anthracite coal in this plant, we conducted calorific value analysis using a holistic-segmented model, and the test results met the application requirements.
— This study aims to develop predictive models for the HHV of coal using machine learning techniques. To achieve this goal, we designed 17 optimized models, …
— A nation's ability to use its energy resources efficiently and the expansion of its industrial sector are key factors in its prosperity. Most of the industrially developed nations in the world use coal as their main energy source. These resources have been utilized mainly for industrial growth, such as thermal power plants, steel industries, and other …
— The uses of coal in different power generation sectors depend on the quality of coal, such as gross calorific value (GCV), volatile matter (VM), and fixed carbon (FC) content. ... to classify the coal samples. Support Vector Machine (SVM): SVM is one of the most robust classifiers in Machine Learning [21]. Support vector machine is a linear ...
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}, …
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 …
— A total of 28 certified coal samples that purchased from Jinan Zhongbiao Technologies Co Ltd. in the form of powder were used in this study. The certified calorific value of the studied coal samples were listed in Table 1.Since the accuracy and precision of LIBS were heavily affected by the inhomogeneity of the sample, all powder samples …
— Calorific value prediction of coal and its optimization by machine learning based on limited samples in a wide range. April 2023. Energy 277 (6):127666. DOI:...
— These correlations and machine learning prediction tools tend to be too complex and hence are of limited utility for the end-user. ... The gross calorific value (GCV) of coal is a key yardstick ...
— 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. ...
— In energy scarcity, particularly in Agri-based developing economies, bio-coal briquetting is the most suitable means of meeting sustainable energy needs utilizing agricultural waste. In this study, briquettes were made from an indigenously designed briquetting machine for investigating coal–biomass proportion blend using coal from …
— 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 ...
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.
— 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 …
— Request PDF | Machine learning prediction of calorific value of coal based on the hybrid analysis | As one of the most important indicators of coal, calorific value (CV) not only determines the ...
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 …
— 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 ...
Rapid determination of the gross calorific value of coal using laser-induced breakdown spectroscopy coupled with artificial neural networks and genetic algorithm.
— Calorific value is an important index for evaluating coal quality, and it is important to achieve the rapid detection of calorific value to improve production efficiency. In this paper, a calorific value detection method based on NIRS-XRF fusion spectroscopy is proposed, which utilizes NIRS to detect organic functional groups and XRF to detect …
— 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 …
— 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, …
— The direct gas content determination methods subdivide the total gas content of a coal sample into three components [12].These components are defined as lost (Q 1), desorbed (Q 2) and residual (Q 3) gas.The Q 1 is gas lost from the samples subsequent to its removal from its in-situ position and prior to its containment in the canister. Q 2 is the …
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.
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 ...
— As an indicative standard for coal stored energy, gross calorific value (GCV) has been modeled by many different artificial intelligence "AI" methods such as a feed-forward artificial neural network (FANN), random forest (RF), and support vector regression (SVR) (GCV could be considered for the primary evaluation of coal prices) (Chelgani ...
— The calorific value of coal is measured for almost all coal samples. It is a measure of the heating ability of a coal and is needed to estimate the amount of coal needed to produce a desired amount of heat. ... Calorific value can be measured in standard English units (Btu/lb) or in metric units (kilojoules/kg or megajoules/kg). One …
— 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.
— 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 ...
— 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 warming, …
