Decision tree regression model to predict low-rank coal moisture content during convective drying process-Reference-Cited by-同舟云学术

Decision tree regression model to predict low-rank coal moisture content during convective drying process

Published:2020-03-13 Issue:8 Volume:40 Page:505-512
ISSN:1939-2699
Container-title:International Journal of Coal Preparation and Utilization
language:en
Short-container-title:International Journal of Coal Preparation and Utilization

Author:

Pekel Engin¹^ORCID,Akkoyunlu Mehmet Cabir²^ORCID,Akkoyunlu Mustafa Tahir³^ORCID,Pusat Saban⁴^ORCID

Affiliation:

1. Department of Industrial Engineering, Hitit University, Çorum, Turkey

2. Department of Mechanical and Metal Technology, Karamanoglu Mehmetbey University, Karaman, Turkey

3. Department of Energy Systems Engineering, Necmettin Erbakan University, Meram, Konya, Turkey

4. Department of Mechanical Engineering, Yildiz Technical University, Istanbul, Turkey

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Energy Engineering and Power Technology,Geotechnical Engineering and Engineering Geology,Fuel Technology,General Chemical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/19392699.2020.1737527

Reference18 articles.

1. Determination of Effective Parameters for Coal Moisture Content Determination Using a ‘Design of Experiment’ Method

2. Moisture content estimation during fixed bed drying process with design of experiment and ANFIS methods

3. Determination of economic upper limit of drying processes in coal-fired power plants

4. Prediction of Accurate Values for Outliers in Coal Drying Experiments

5. Prediction of coal grindability based on petrography, proximate and ultimate analysis using multiple regression and artificial neural network models

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