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Application of real valued genetic algorithm on prediction of higher heating values of various lignocellulosic materials using lignin and extractive contents

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dc.creator Akdeniz, Fikret
dc.creator Bicil, Metin
dc.creator KARADEDE, Yusuf
dc.creator Ozbek, Fureya Elif
dc.creator ÖZDEMİR, Gültekin
dc.date 2018-09-30T21:00:00Z
dc.date.accessioned 2020-10-06T09:43:28Z
dc.date.available 2020-10-06T09:43:28Z
dc.identifier 34d4bbc4-a194-460e-9c69-34c6b99ff03f
dc.identifier 10.1016/j.energy.2018.07.053
dc.identifier https://avesis.sdu.edu.tr/publication/details/34d4bbc4-a194-460e-9c69-34c6b99ff03f/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/57145
dc.description The higher heating values (HHVs) of 11 non-wood lignocellulosic materials from Turkey were measured experimentally and calculated incorporating various theoretical models with the values of both lignin and extractive contents. Multiple linear regression (MLR) and real valued genetic algorithm (RVGA) were used to derive the theoretical models. A non-linear RVGA6 model was determined as the best non-linear model considering the experimental results with a regression coefficient of 92% coefficient of determination (R-2), 0.301 sum of squared errors (SSE), 0301 mean squared errors (MSE), 0.548 root mean squared errors (RMSE) and 0.0187 mean absolute percentage error (MAPE) and is proposed as a better alternative for theoretical HHV calculations to the multiple linear modellings such as MLR and RVGAl. (C) 2018 Elsevier Ltd. All rights reserved.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Application of real valued genetic algorithm on prediction of higher heating values of various lignocellulosic materials using lignin and extractive contents
dc.type info:eu-repo/semantics/article


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