2020
DOI: 10.3390/app10186432
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Estimating the Heat Capacity of Non-Newtonian Ionanofluid Systems Using ANN, ANFIS, and SGB Tree Algorithms

Abstract: This work investigated the capability of multilayer perceptron artificial neural network (MLP–ANN), stochastic gradient boosting (SGB) tree, radial basis function artificial neural network (RBF–ANN), and adaptive neuro-fuzzy inference system (ANFIS) models to determine the heat capacity (Cp) of ionanofluids in terms of the nanoparticle concentration (x) and the critical temperature (Tc), operational temperature (T), acentric factor (ω), and molecular weight (Mw) of pure ionic liquids (ILs). To this end, a comp… Show more

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Cited by 36 publications
(14 citation statements)
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References 80 publications
(94 reference statements)
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“…Another statistical method used in this study is outlier diagnosis. This method is considered a fundamental method applied to determine datasets with different behavior from all data [ 41 , 42 ]. It uses leverage statistical technique to find the outliers having parameters such as standardized residuals ( R ), critical leverage limit ( H ∗ ), and Hat indices ( H ) [ 43 , 44 ].…”
Section: Resultsmentioning
confidence: 99%
“…Another statistical method used in this study is outlier diagnosis. This method is considered a fundamental method applied to determine datasets with different behavior from all data [ 41 , 42 ]. It uses leverage statistical technique to find the outliers having parameters such as standardized residuals ( R ), critical leverage limit ( H ∗ ), and Hat indices ( H ) [ 43 , 44 ].…”
Section: Resultsmentioning
confidence: 99%
“…In recent years, a minority of estimated models such as artificial intelligence methods have been executed to evaluate material properties and processes in different applications [27][28][29][30][31][32][33]. Recently, with extensive development in technology and science, some novel and smart methods are suggested such as GMDH (Group Method of Data Handling), GPR, ANFIS, ANN, and LSSVM; by means of these useful methods, many complex and nonlinear problems can be modelled in many different branches [34][35][36][37][38].…”
Section: Introductionmentioning
confidence: 99%
“…The lack of sufficient accuracy and difficulties of computations cause more attention in the aforementioned literature. On the other hand, much attention has been paid to artificial intelligence methods to a precise solution in order to model different processes [28][29][30][31][32][33]. One of the things that are crucial for the process design and the same operation is the accuracy of thermophysical properties.…”
Section: Introductionmentioning
confidence: 99%