Utilization of apricot seed in (co-)combustion of lignite coal blends: Numeric optimization, empirical modeling and uncertainty estimation

Utilization of apricot seed in (co-)combustion of lignite coal blends: Numeric optimization,... Fuel 216 (2018) 190–198 Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Utilization of apricot seed in (co-)combustion of lignite coal blends: Numeric optimization, empirical modeling and uncertainty estimation a, b Musa Buyukada , Ercan Aydogmus Department of Environmental Engineering, Abant Izzet Baysal University, Bolu 14280, Turkey Department of Chemical Engineering, Fırat University, Elazığ 23200, Turkey GR APHICAL A BSTRACT ARTICLE I NFO ABSTRACT Keywords: Utilization of apricot seed (AS) in lignite coal (LC)-based (co-)combustion process was aimed in the present study Co-combustion considering the apricot production capacity of Turkey. By this way, an alternative and also ecofriendly way was Multiple nonlinear regression suggested for coal-based energy production plants located in Turkey. This purpose was tested by thermogravi- Artificial neural networks metric analyses to demonstrate the advantageous sides of AS in reduction of ash amount and also environmental Response surface methodology aspects based on harmful gases. The other important contributors of present study was the comparison of both Particle swarm optimization statistical modeling and numeric optimization techniques for maximization of mass loss percentage (MLP, %) in Bayesian approach response to (co-)combustion process. For this purpose, multiple non-linear regression (MNLR) and artificial neural network (ANN) models http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuel Elsevier

Utilization of apricot seed in (co-)combustion of lignite coal blends: Numeric optimization, empirical modeling and uncertainty estimation

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0016-2361
D.O.I.
10.1016/j.fuel.2017.12.028
Publisher site
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Abstract

Fuel 216 (2018) 190–198 Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Utilization of apricot seed in (co-)combustion of lignite coal blends: Numeric optimization, empirical modeling and uncertainty estimation a, b Musa Buyukada , Ercan Aydogmus Department of Environmental Engineering, Abant Izzet Baysal University, Bolu 14280, Turkey Department of Chemical Engineering, Fırat University, Elazığ 23200, Turkey GR APHICAL A BSTRACT ARTICLE I NFO ABSTRACT Keywords: Utilization of apricot seed (AS) in lignite coal (LC)-based (co-)combustion process was aimed in the present study Co-combustion considering the apricot production capacity of Turkey. By this way, an alternative and also ecofriendly way was Multiple nonlinear regression suggested for coal-based energy production plants located in Turkey. This purpose was tested by thermogravi- Artificial neural networks metric analyses to demonstrate the advantageous sides of AS in reduction of ash amount and also environmental Response surface methodology aspects based on harmful gases. The other important contributors of present study was the comparison of both Particle swarm optimization statistical modeling and numeric optimization techniques for maximization of mass loss percentage (MLP, %) in Bayesian approach response to (co-)combustion process. For this purpose, multiple non-linear regression (MNLR) and artificial neural network (ANN) models

Journal

FuelElsevier

Published: Mar 15, 2018

References

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