Comparison of LSSVM model results with artificial neural network model for determination of the solubility of SO2 in ionic liquids

Mokarizadeh, Hadi; Atashrouz, Saeid; Mirshekar, Hamed; Hemmati-Sarapardeh, Abdolhossein; Pour, Ahmad Mohaddes

doi:10.1016/j.molliq.2020.112771

Cited by 40 publications

(20 citation statements)

References 48 publications

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“…The basic objective was to conduct a comparative analysis between model yields and real values. The accuracy of the model's accuracy is improved when the fitted line approaches the bisector line [ 39 , 40 ]. A remarkable linear correlation is achieved between the model outputs and actual values for R 2 = 1, which gets weaker when the R 2 value approaches to zero [ 41 , 42 ].…”

Section: Resultsmentioning

confidence: 99%

Implementing PSO-ELM Model to Approximate Trolox Equivalent Antioxidant Capacity as One of the Most Important Biological Properties of Food

Elveny

Akhmadeev

Dinari

et al. 2021

BioMed Research International

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In this paper, the Trolox equivalent antioxidant capacity (TEAC) is estimated through a robust machine-learning algorithm known as the Particle Swarm Optimization-based Extreme Learning Machine (PSO-ELM) model. For this purpose, a large dataset from previously published reports was gathered. Various analyses were performed to evaluate the proposed model. The results of the statistical analysis showed that this model can predict the actual values with high accuracy, so that the calculated R 2 and RMSE values were equal to 0.973 and 3.56, respectively. Sensitivity analysis was also performed on the effective input parameters. The leverage technique was also performed to check the accuracy of real data, and the results showed that the majority of data are reliable. This simple yet accurate model can be very powerful in predicting the Trolox equivalent antioxidant capacity values and can be a good alternative to laboratory data.

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Section: Resultsmentioning

confidence: 99%

Implementing PSO-ELM Model to Approximate Trolox Equivalent Antioxidant Capacity as One of the Most Important Biological Properties of Food

Elveny

Akhmadeev

Dinari

et al. 2021

BioMed Research International

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“…The Williams plot was applied in order to investigate the outliers after the measurement of the R and Hat index ( H ) [ 107 , 108 ]. In this diagram, the standardized residuals are sketched against Hats.…”

Section: Resultsmentioning

confidence: 99%

Viscosity of Ionic Liquids: Application of the Eyring’s Theory and a Committee Machine Intelligent System

et al. 2020

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Accurate determination of the physicochemical characteristics of ionic liquids (ILs), especially viscosity, at widespread operating conditions is of a vital role for various fields. In this study, the viscosity of pure ILs is modeled using three approaches: (I) a simple group contribution method based on temperature, pressure, boiling temperature, acentric factor, molecular weight, critical temperature, critical pressure, and critical volume; (II) a model based on thermodynamic properties, pressure, and temperature; and (III) a model based on chemical structure, pressure, and temperature. Furthermore, Eyring’s absolute rate theory is used to predict viscosity based on boiling temperature and temperature. To develop Model (I), a simple correlation was applied, while for Models (II) and (III), smart approaches such as multilayer perceptron networks optimized by a Levenberg–Marquardt algorithm (MLP-LMA) and Bayesian Regularization (MLP-BR), decision tree (DT), and least square support vector machine optimized by bat algorithm (BAT-LSSVM) were utilized to establish robust and accurate predictive paradigms. These approaches were implemented using a large database consisting of 2813 experimental viscosity points from 45 different ILs under an extensive range of pressure and temperature. Afterward, the four most accurate models were selected to construct a committee machine intelligent system (CMIS). Eyring’s theory’s results to predict the viscosity demonstrated that although the theory is not precise, its simplicity is still beneficial. The proposed CMIS model provides the most precise responses with an absolute average relative deviation (AARD) of less than 4% for predicting the viscosity of ILs based on Model (II) and (III). Lastly, the applicability domain of the CMIS model and the quality of experimental data were assessed through the Leverage statistical method. It is concluded that intelligent-based predictive models are powerful alternatives for time-consuming and expensive experimental processes of the ILs viscosity measurement.

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“…On the country, CO 2 solubility in ILs represents an opposite behavior against critical pressure. In other words, CO 2 solubility lowers by increasing critical pressure (Hemmati-Sarapardeh et al, 2020;Menad et al, 2019;Mokarizadeh et al, 2020). In order to compare the experimental and predicted result values and check the physical validity of the proposed model, variation of CO 2 solubility in one ionic liquid ([bmim][Tf2N]) against input parameters of pressure and temperature was investigated in Figure 8.…”

Section: Resultsmentioning

confidence: 99%

Modeling of carbon dioxide solubility in ionic liquids based on group method of data handling

Moosanezhad-Kermani

Rezaei

Hemmati-Sarapardeh

et al. 2020

Engineering Applications of Computational Fluid Mechanics

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Comparison of LSSVM model results with artificial neural network model for determination of the solubility of SO2 in ionic liquids

Cited by 40 publications

References 48 publications

Implementing PSO-ELM Model to Approximate Trolox Equivalent Antioxidant Capacity as One of the Most Important Biological Properties of Food

Implementing PSO-ELM Model to Approximate Trolox Equivalent Antioxidant Capacity as One of the Most Important Biological Properties of Food

Viscosity of Ionic Liquids: Application of the Eyring’s Theory and a Committee Machine Intelligent System

Modeling of carbon dioxide solubility in ionic liquids based on group method of data handling

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