Prediction of gross calorific value from coal …
Rapid determination of the gross calorific value of coal using laser-induced breakdown spectroscopy coupled with artificial neural networks and genetic algorithm.
Utilization of Biowaste for Sustainable Production of Coal …
— 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 …
Proximate analysis based prediction of gross calorific value …
— The calorific value of coal is of great importance in both its direct use and the conversion to other useful forms of fuel [7]. The calorific value is usually expressed as gross calorific value (GCV) or higher heating value (HHV). ... Support vector machine based online coal identification through advanced flame monitoring. Fuel, 117 (2014), pp ...
Calorific value prediction of coal and its …
— 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:...
Machine learning prediction of calorific value of coal based …
— 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 ...
Accurate analysis of coal calorific value using NIRS-XRF: …
— 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.
Rapid quantitative analysis of coal composition using laser …
— 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 …
Prediction of coal self-ignition tendency using machine …
— In addition, histograms of the 13 input features (proximate analysis, ultimate analysis, coal calorific value, coal particle size, ambient temperature, oxygen concentration) and CPT were shown in Fig. 2. 204 samples were divided into 142 (70%) samples and 62 (30%) samples as training set and testing set to train the fitting and generalization ...
Briquette production and performance evaluation from coal …
— 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, …
Coal Calorific Value Detection Technology Based on NIRS …
— 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 …
Estimation of gross calorific value based on coal analysis …
— 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 ...
Calorific value prediction of coal and its optimization by machine …
— Request PDF | Calorific value prediction of coal and its optimization by machine learning based on limited samples in a wide range | Measuring the heating value through experimentation is a ...
Prediction of Gross Calorific Valueof Coal using …
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
Accurate analysis of coal calorific value using NIRS-XRF: …
— Rapid and precise measurement of the calorific value of coal is crucial for coal chemical enterprises. However, due to the wide variety of coal sources and the diverse …
Prediction of gross calorific value as a function of proximate
— 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 ...
Estimation of gross calorific value of coal: A literature review
— 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 …
Determining the Gross Calorific Value in Coal
— 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 …
A data-driven approach for the prediction of coal seam gas …
— 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 …
Modeling of gross calorific value based on coal properties …
— 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 …
Prediction of Coal Calorific Value Based on a Hybrid Linear …
— 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. ...
Estimation of gross calorific value of coal: A literature review
— 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 …
Calorific Value Prediction of Coal Based on Least Squares …
— Least squares support vector machine (LSSVM) is a variation of the classical SVM, which has minimal computational complexity and fast calculation. This paper …
Proximate analysis based prediction of gross calorific value …
— This paper presents the application of three regression models, i.e., support vector machine (SVM), alternating conditional expectation (ACE) and back propagation …
Estimation of coal gross calorific value based on various …
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 …
Research on New Nonlinear Method Applied on Coal Calorific …
— 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 …
Calorific value prediction of coal and its optimization by machine …
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}, …
Prediction models of calorific value of coal based on …
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}, …
Rapid Determination of Gross Calorific Value of Coal Using …
— 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 …
Fast and Nondestructive Proximate Analysis of Coal from
— 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, …
A near-infrared spectroscopy dataset of coal and coal …
— 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 ...
Quantitative Analysis of Calorific Value of Coal Based on …
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 …
Machine learning prediction of calorific value of coal based …
— 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 …
Calorific value prediction of coal and its optimization by machine …
— 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].
Calorific value prediction of coal and its optimization by …
— 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, …