Adsorption modeling and optimization of thorium (IV) ion from aqueous solution using chitosan/TiO2 nanocomposite: Application of artificial neural network and genetic algorithm

Broujeni, B. Rouhi; Nilchi, A.; Azadi, Fatemeh

doi:10.1016/j.enmm.2020.100400

Cited by 10 publications

(8 citation statements)

References 67 publications

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“…Several physicochemical processes such as initial concentration, pH, time, etc. have an impact on the adsorption process (Broujeni et al, 2021). In this work, in which the adsorption efficiencies of MB concentrations by T. barbata were examined; the effects of contact time, initial dye concentration, and adsorbent concentration were studied.…”

Section: Resultsmentioning

confidence: 99%

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Prediction models of dye adsorption by Treptacantha barbata

Tunca¹,

Şirin²,

Türe³

2022

EgeJFAS

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This study's objective was to develop a model to determine dye adsorption efficiency of Treptacantha barbata (Stackhouse) Orellana& Sansón, 2019 (formerly Cystoseira barbata (Stackhouse) C. Agardh, 1820). During the experiments, treatment groups, such as initial dye Methylene Blue (MB) concentration (0.1-10.0 mg L-1), contact time (5 to 1440 min) and adsorbent dosage (0.1-2 g) were applied. Scanning electron microscopy, energy dispersive X-ray, and Fourier Transform Infrared Spectroscopy were used to analyze the adsorbent. T. barbata was found to be quite successful in removing dye (69% -100%) for all experiments, and the qe values increased with the increased the initial dye concentration. Very rapid dye removal was detected during the first contact time, especially up to 15 min. Isotherms, kinetics, and regression models were applied to the batch experimental results. The results displayed that adsorption process was suitable with the Langmuir isotherm model (R2: 0.97).

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Section: Resultsmentioning

confidence: 99%

“…Using the following equations, MB removal effectiveness and adsorption capacity were estimated. (Naushad et al, 2015;Zhang et al, 2016;Broujeni et al, 2021;Renita et al, 2021).…”

Section: Sorption Experimentsmentioning

confidence: 99%

Prediction models of dye adsorption by Treptacantha barbata

Tunca¹,

Şirin²,

Türe³

2022

EgeJFAS

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“…The iterative cycle is maintained until the desired solution is reached before termination. The algorithm can be implemented in a Matlab environment [74][75][76][77][78].…”

Section: Genetic Algorithmmentioning

confidence: 99%

Evaluation of Heterocyclic Aromatic Compound Dye (Methylene Blue) on Chitosan Adsorbent Sourced from African Snail Shell: Modelling and Optimization Studies

Bello

Olafadehan

2022

J. Appl. Sci. Process Eng.

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In this article, the modelling and optimization of five operational process parameters involving initial concentration, adsorbent dosage, contact time, temperature and pH of the solution as it affects the treatment of aqueous solution contaminated with methylene blue, a heterocyclic aromatic compound, on chitosan sourced from African Snail Shell were studied using response surface methodology (RSM) and artificial neural network (ANN) techniques coupled with genetic algorithm. The single and interactive effects of the variables were examined by way of analysis of variance (ANOVA). A comparison of the model techniques was done and an evaluation was carried out with some selected error functions. Both modelling and optimization tools performed creditably well. However, the hybrid ANN-GA proved to be a superior modelling and optimization technique with excellent generalization ability which gave an average absolute deviation between the experimental and predicted data of both response variables considered. The insightful relative importance of the process variables based on the renowned Garson and Olden’s algorithm methods coupled with step by step approach initiated in the Matlab environment were equally investigated. The findings from this study revealed in clear terms that pH and initial concentrations were the most influential parameters and the maximum value of 99.28% of methylene blue removed at optimum conditions affirmed that the chitosan adsorbent is viable for the treatment of effluents from the textile industry.

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“…In 2006, Professor Hinton [24] provided an effective algorithm for initializing weights, which led to the development of deep learning in the field of research and applications [25][26][27] .…”

Section: The Principle and Application Development Of Neural Networkmentioning

confidence: 99%

Study on the Simulation Control of Neural Network Algorithm in Thermally Coupled Distillation

Zheng

2021

AJRCoS

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Thermally coupled distillation is a new energy-saving method, but the traditional thermally coupled distillation simulation calculation process is complicated, and the optimization method based on the traditional simulation process is difficult to obtain a good feasible solution. The neural network algorithm has the advantages of fast learning and can approach nonlinear functions arbitrarily. For the problems in complex process control systems, neural network control does not require cumbersome control structures or precise mathematical models. When training the network, only the input and output samples it needs are given, so that the dynamics of the system can be controlled. In this way, the dynamic performance of the system can be approximated. This method can effectively solve the mathematical model of the thermally coupled distillation process, and quickly obtain the solution of the optimized variables and the objective function. This article summarizes the research progress of artificial neural network and the optimization control of thermally coupled distillation and the application of neural network in thermally coupled distillation.

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Adsorption modeling and optimization of thorium (IV) ion from aqueous solution using chitosan/TiO2 nanocomposite: Application of artificial neural network and genetic algorithm

Cited by 10 publications

References 67 publications

Prediction models of dye adsorption by Treptacantha barbata

Prediction models of dye adsorption by Treptacantha barbata

Evaluation of Heterocyclic Aromatic Compound Dye (Methylene Blue) on Chitosan Adsorbent Sourced from African Snail Shell: Modelling and Optimization Studies

Study on the Simulation Control of Neural Network Algorithm in Thermally Coupled Distillation

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