TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES· 2018Q2
Prediction of gross calorific value of coal based on proximate analysis using multiple linear regression and artificial neural networks
- 35citations
- Q2SCImago
- 2018year
Short summary
Radial Basis Function Neural Networks (RBFNN) achieved high performance in predicting coal's gross calorific value (GCV) from proximate analysis data, outperforming other neural networks and multiple linear regression.
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