Application of least squares support vector regression and linear multiple regression for modeling removal of methyl orange onto tin oxide nanoparticles loaded on activated carbon and activated carbon prepared from  Pistacia atlantica  wood

Ghaedi, Mehrorang; Rahimi, Mahmood Reza; Ghaedi, A.M.; Tyagi, Inderjeet; Agarwal, Shilpi; Gupta, Vinod Kumar

doi:10.1016/j.jcis.2015.09.024

Cited by 105 publications

(23 citation statements)

References 52 publications

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“…There are several adsorbents such as sensors and electrochemical electrodes [14][15][16][17][18], bagasse fly ash [19,20], bottom ash [21,22], CNTs and MWCNTs [23][24][25][26][27][28][29][30], fix bed adsorbers [31], resins [32], nanoparticles [33][34][35][36][37][38][39], and rubber tire [40][41][42], these all and the previously developed adsorbents have various applications in many scientific and industrial fields, including wastewater purification, heavy metal ion removal and hazardous impurities.…”

Section: Introductionmentioning

confidence: 99%

Microporous nanocrystalline NaA zeolite prepared by microwave assisted hydrothermal method and determination of kinetic, isotherm and thermodynamic parameters of the batch sorption of Ni (II)

Ghasemi

Javadian

Ghasemi

et al. 2016

Journal of Molecular Liquids

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Section: Introductionmentioning

confidence: 99%

Microporous nanocrystalline NaA zeolite prepared by microwave assisted hydrothermal method and determination of kinetic, isotherm and thermodynamic parameters of the batch sorption of Ni (II)

Ghasemi

Javadian

Ghasemi

et al. 2016

Journal of Molecular Liquids

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“…In order to investigate the kinetic adsorption of of dye on as-prepared samples, the pseudo-first-order model [13] and pseudo-second-order kinetic model [14] were used and described in equation of (4) and 5, respectively.…”

Section: Adsorption Experimentsmentioning

confidence: 99%

Preparation of flower‐like Cu₂O/ZnO for removal of dyes from aqueous medium

Dat

Hung

Tuấn

2020

Vietnam Journal of Chemistry

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Flower‐like Cu2O/ZnO was prepared by hydrothermal method with the reducing agent of glucose for removal of dyes in aqueous medium. As‐prepared samples were characterized by FE‐SEM, XRD, and TEM. Flower‐like Cu2O/ZnO could both photodegrade Tartrazine (TA) under UV and visible lights with the removal efficiencies of 85.3 and 96.1 %, respectively, and adsorbed TA with the removal efficiency of 77.5 %. The effects of adsorbent dosage, dye concentration, and pH solution on adsorption of dyes were investigated. The kinetic adsorption of TA on flower‐like Cu2O/ZnO was studied by pseudo‐first‐order and pseudo‐second‐order models. In addition, the performance of as‐prepared material was evaluated by cyclic test and adsorption of other dyes such as methylene blue, Janus green B and Congo red.

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“…Compared with the general kernel functions, Gauss kernel function only needs to determine a parameter, and constructing the kernel function model is relatively simple. Therefore, RBF kernel function is currently the most widely used one [30]. Sigmoid kernel function:…”

Section: Thmentioning

confidence: 99%

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

Wang

2017

Journal of Control Science and Engineering

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Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF) support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

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Application of least squares support vector regression and linear multiple regression for modeling removal of methyl orange onto tin oxide nanoparticles loaded on activated carbon and activated carbon prepared from Pistacia atlantica wood

Cited by 105 publications

References 52 publications

Microporous nanocrystalline NaA zeolite prepared by microwave assisted hydrothermal method and determination of kinetic, isotherm and thermodynamic parameters of the batch sorption of Ni (II)

Microporous nanocrystalline NaA zeolite prepared by microwave assisted hydrothermal method and determination of kinetic, isotherm and thermodynamic parameters of the batch sorption of Ni (II)

Preparation of flower‐like Cu₂O/ZnO for removal of dyes from aqueous medium

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

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Application of least squares support vector regression and linear multiple regression for modeling removal of methyl orange onto tin oxide nanoparticles loaded on activated carbon and activated carbon prepared from Pistacia atlantica wood

Cited by 105 publications

References 52 publications

Microporous nanocrystalline NaA zeolite prepared by microwave assisted hydrothermal method and determination of kinetic, isotherm and thermodynamic parameters of the batch sorption of Ni (II)

Microporous nanocrystalline NaA zeolite prepared by microwave assisted hydrothermal method and determination of kinetic, isotherm and thermodynamic parameters of the batch sorption of Ni (II)

Preparation of flower‐like Cu2O/ZnO for removal of dyes from aqueous medium

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

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Product

Resources

About

Preparation of flower‐like Cu₂O/ZnO for removal of dyes from aqueous medium