On the evaluation of solubility of hydrogen sulfide in ionic liquids using advanced committee machine intelligent systems
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- @Article{NAITAMAR:2021:JTICEa,
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author = "Menad {Nait Amar} and Mohammed Abdelfetah Ghriga and
Hocine Ouaer",
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title = "On the evaluation of solubility of hydrogen sulfide in
ionic liquids using advanced committee machine
intelligent systems",
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journal = "Journal of the Taiwan Institute of Chemical
Engineers",
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volume = "118",
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pages = "159--168",
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year = "2021",
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ISSN = "1876-1070",
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DOI = "doi:10.1016/j.jtice.2021.01.007",
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URL = "https://www.sciencedirect.com/science/article/pii/S1876107021000080",
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keywords = "genetic algorithms, genetic programming, Hydrogen
sulfide, Ionic liquids, Solubility, Data-driven,
Committee machine intelligent systems",
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abstract = "Ionic Liquids (ILs) are increasingly emerging as new
innovating green solvents with great importance from
academic, industrial, and environmental perspectives.
This surge of interest in considering ILs in various
applications is owed to their attractive properties.
Involvements in the gas sweetening and the reduction of
the amounts of sour and acid gasses are among the most
promising applications of ILs. In this study, new
advanced committee machine intelligent systems (CMIS)
were introduced for predicting the solubility of
hydrogen sulfide (H2S) in various ILs. The implemented
CMIS models were gained by linking robust data-driven
techniques, namely multilayer perceptron (MLP) and
cascaded forward neural network (CFNN) beneath rigorous
schemes using group method of data handling (GMDH) and
genetic programming (GP). The proposed paradigms were
developed using an extensive database encompassing 1243
measurements of H2S solubility in 33 ILs. The performed
comprehensive error investigation revealed that the
newly implemented paradigms yielded very satisfactory
prediction performance. Besides, it was found that
CMIS-GP provided more accurate estimations of H2S
solubility in ILs compared with both the other
intelligent models and the best-prior paradigms. In
this regard, the developed CMIS-GP exhibited overall
average absolute relative deviation (AARD) and
coefficient of determination (R2) values of
2.3767percent and 0.9990, respectively. Lastly, the
trend analyses demonstrated that the tendencies of
CMIS-GP predictions were in excellent accordance with
the real variations of H2S solubility in ILs with
respect to pressure and temperature",
- }
Genetic Programming entries for
Menad Nait Amar
Mohammed Abdelfetah Ghriga
Hocine Ouaer
Citations