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Prediction of Air Specific Heat Ratios at Elevated Pressures Using a Novel Modeling Approach
Author(s) -
Kamari Arash,
Mohammadi Amir H.,
Bahadori Alireza,
Zendehboudi Sohrab
Publication year - 2014
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201400261
Subject(s) - applicability domain , leverage (statistics) , support vector machine , simulated annealing , least squares support vector machine , computer science , mathematics , biological system , algorithm , statistics , artificial intelligence , machine learning , quantitative structure–activity relationship , biology
An accurate and efficient model based on least‐squares support vector machines (LSSVM) is developed for the determination of air specific heat ratios at elevated pressures. Additionally, the coupled simulated annealing optimization strategy is used to calculate the optimal values of the LSSVM parameters. A large dataset of air specific heat ratios as a function of temperature and pressure for about 170 samples is used to develop and validate the model. The leverage approach (Williams plot) is used to determine the applicability domain of the model and to detect probably erroneous data points. Comparison of the obtained results with a previously published correlation as well as an intelligent method demonstrates that the performance of the presented model is more satisfactory than that of other methods.