A simple modelling approach for prediction of standard state real gas entropy of pure materials
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- @Article{Bagheri:2015:SAR_QSAR_ER,
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author = "M. Bagheri and T. N. G. Borhani and A. H. Gandomi and
Z. A. Manan",
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title = "A simple modelling approach for prediction of standard
state real gas entropy of pure materials",
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journal = "SAR and QSAR in Environmental Research",
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year = "2014",
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volume = "25",
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number = "9",
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pages = "695--710",
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keywords = "genetic algorithms, genetic programming, linear
genetic programming (LGP), standard state absolute
entropy of real gases (SSTD), feed forward neural
network (FFNN), quantitative structure entropy
relationship, exergy analysis",
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URL = "http://www.tandfonline.com/doi/abs/10.1080/1062936X.2014.942356",
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URL = "http://www.tandfonline.com/doi/full/10.1080/1062936X.2014.942356",
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DOI = "doi:10.1080/1062936X.2014.942356",
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abstract = "The performance of an energy conversion system depends
on exergy analysis and entropy generation minimisation.
A new simple four-parameter equation is presented in
this paper to predict the standard state absolute
entropy of real gases (SSTD). The model development and
validation were accomplished using the Linear Genetic
Programming (LGP) method and a comprehensive dataset of
1727 widely used materials. The proposed model was
compared with the results obtained using a three-layer
feed forward neural network model (FFNN model). The
root-mean-square error (RMSE) and the coefficient of
determination (r2) of all data obtained for the LGP
model were 52.24 J/(mol K) and 0.885, respectively.
Several statistical assessments were used to evaluate
the predictive power of the model. In addition, this
study provides an appropriate understanding of the most
important molecular variables for exergy analysis.
Compared with the LGP based model, the application of
FFNN improved the r-squared to 0.914. The developed
model is useful in the design of materials to achieve a
desired entropy value.",
- }
Genetic Programming entries for
Mehdi Bagheri
Tohid Nejad Ghaffar Borhani
A H Gandomi
Zainuddin Abdul Manan
Citations