Journal ArticleDOI
The use of artificial neural networks (ANN) for modeling of adsorption of Cr(VI) ions
TLDR
In this article, an artificial neural network (ANN) based technique is applied for the prediction of the percentage removal of Cr(VI) ions from aqueous solution using eight different natural biosorbents.Abstract:
In this study, an artificial neural network (ANN) based techniques is applied for the prediction of the percentage removal of Cr(VI) ions from aqueous solution using eight different natural biosorbents. The effects of operating parameters such as initial pH, initial Cr(VI) ion concentration, adsorbent dosages, and contact time are studied to optimize the conditions for maximum removal of Cr(VI) ions. The ANN with a single hidden layer trained with Levenberg-Marquardt algorithm predicted the percentage removal of Cr(VI) ions from aqueous solution accurately.read more
Citations
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Development of artificial intelligence for modeling wastewater heavy metal removal: State of the art, application assessment and possible future research
TL;DR: In this review, each element of the predictive models and their corresponding treatment processes, including its pros and cons, are discussed thoroughly and several research directions, which could bridge the gap in the same domain are proposed and recommended on the basis of the identified research limitations.
Journal ArticleDOI
Biosorption of chromium (VI) from aqueous solutions and ANN modelling
TL;DR: The study explores the undiscovered potential of the natural waste materials for sustainable existence of small and medium sector industries, especially in the third world countries by protecting the environment by eco-innovation.
Journal ArticleDOI
The use of artificial neural network (ANN) for modeling of Pb(II) adsorption in batch process
TL;DR: In this article, the effects of different operating parameters such as initial pH, initial Pb(II) ion concentration, adsorbent dosages, and contact time are studied to optimize the conditions for maximum batch adsorptive removal of PbII ions from aqueous solution using six different low cost natural bio-sorbents.
Journal ArticleDOI
Removal of Cr(VI) from Its Aqueous Solution Using Green Adsorbent Pistachio Shell: a Fixed Bed Column Study and GA-ANN Modeling
TL;DR: Yan et al. as mentioned in this paper used pistachio shells as green and eco-friendly adsorbent for Cr(VI) adsorption, and applied GA-ANN hybrid model to predict the percentage removal.
References
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Journal ArticleDOI
An introduction to computing with neural nets
TL;DR: This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification and exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components.
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Cr(VI) and Cr(III) removal from aqueous solution by raw and modified lignocellulosic materials: a review.
TL;DR: This study is a review of the recent literature on the use of natural and modified lignocellulosic residues for Cr adsorption and finds that many by-products of agriculture have proved to be suitable low cost adsorbents for Cr(VI) and Cr(III) removal from water.
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Connectionist nonparametric regression: multilayer feedforward networks can learn arbitrary mappings
TL;DR: It is shown that sufficiently complex multilayer feedforward networks are capable of representing arbitrarily accurate approximations to arbitrary mappings by proving the consistency of a class of connectionist nonparametric regression estimators for arbitrary (square integrable) regression functions.
Related Papers (5)
The use of artificial neural network (ANN) for modeling of Pb(II) adsorption in batch process
Biosorption of Cr(VI) ions from aqueous solutions: Kinetics, equilibrium, thermodynamics and desorption studies
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