Results 151 to 160 of about 7,050,556 (197)

Prediction of Calorific Value for Coal Gangue Based on the Machine Learning Algorithm

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Advanced Strategies for Upgrading Raw Biogas into High-Quality Biomethane for Domestic Applications. [PDF]

Bioengineering (Basel)
Kamusoko R, Mukumba P.
europepmc   +1 more source

Evaluating deep coal rock gas fracturing sweet spot intervals using PSO-ELM algorithm and petrophysical logging data. [PDF]

Sci Rep
Liu Z, Wang D, Yang B, Tang J, Wang C, Wang W, Hu X, Zhang J.   +7 more
europepmc   +1 more source

The Optimization of Stand Structure Can Significantly Alleviate the Flammability of Forest Ecosystems. [PDF]

Ecol Evol
Zhang Y, Deng X, He X, Zhang X, Huang Z, Chen L, Ouyang S, Xiang W.   +7 more
europepmc   +1 more source

Estimation of gross calorific value of coal based on the cubist regression model. [PDF]

Sci Rep
Chen J, He Y, Liang Y, Wang W, Duan X.
europepmc   +1 more source

On the Use of Conventional and Soft Computing Models for Prediction of Gross Calorific Value (GCV) of Coal

International Journal of Coal Preparation and Utilization, 2011
Gross calorific value (GCV) is an important characteristic of coal and organic shale; the determination of GCV, however, is difficult, time-consuming, and expensive and is also a destructive analysis. In this article, the use of some soft computing techniques such as ANNs (artificial neural networks) and ANFIS (adaptive neuro-fuzzy inference system ...
Nazan Yalçın Erik, Işık Yılmaz
exaly   +5 more sources

Prediction of Calorific Value of Biomass from Proximate Analysis

Energy Procedia, 2017
Abstract Biomass is one of the renewable and sustainable energy sources that does not lead greenhouse gas emissions. Efficient use of biomass energy will help to solve problems resulting from fossil fuels. However, the main concern relevant to use of this energy is mainly related to low calorific value of biomass.
Serdar Yaman, Ayse Arifoglu
exaly   +2 more sources

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Calorific Value of Coke. 1. Prediction

Coke and Chemistry, 2019
There is great scope for energy conservation in iron production. It is shown that blast furnaces and coke plants are the greatest consumers of energy and carbon in the steel industry. There are not even any optional guidelines for the calorific value of blast-furnace coke produced in Ukraine or elsewhere.
D V Miroshnichenko, I V Shulga
exaly   +2 more sources

Prediction of Calorific Value of Coal by Multilinear Regression and Analysis of Variance

Journal of Energy Resources Technology, 2021
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
M. Sözer, H. Haykiri-Acma, S. Yaman
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Determination of the calorific value of natural gas using predictive modelling

Scientific journal of the Ternopil national technical university, 2021
The analysis of the measured data on the calorific value of natural gas in different regions of Ukraine for 2014–2019, which are in the public domain, has been carried out. Since 2020, such data has not been published. This predetermines the need to use calculation methods for determining this physical quantity for subsequent years in different regions
Halyna Kuz, Leonid Zamikhovskyi, Vitalii Shulha, Mykola Kuz   +3 more
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