January 1, 2017

Application of machine/statistical learning, artificial intelligence and statistical experimental design for the modeling and optimization of methylene blue and Cd(ii) removal from a binary aqueous solution by natural walnut carbon

Key Points

Key points are not available for this paper at this time.

Abstract

We developed and constructed a novel model that could make reliable predictions on the adsorption of methylene blue dye and Cd2+ions from an aqueous medium.

KI fragen

Bookmark

Cite This Study

Mazaheri et al. (Sun,) studied this question.

synapsesocial.com/papers/6a12c26b8f1bac20a09e4059 https://doi.org/https://doi.org/10.1039/c6cp08437k

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Simultaneous removal of Cd(II) and Sb(V) by Fe–Mn binary oxide: Positive effects of Cd(II) on Sb(V) adsorption2015 · 103 citations
2Greedy function approximation: A gradient boosting machine.2001 · 29,108 citations
3Rapid and high-capacity ultrasonic assisted adsorption of ternary toxic anionic dyes onto MOF-5-activated carbon: Artificial neural networks, partial least squares, desirability function and isotherm and kinetic study2016 · 103 citations
4Arcing classifier (with discussion and a rejoinder by the author)1998 · 1,105 citations
5Modeling batch and column phosphate removal by hydrated ferric oxide-based nanocomposite using response surface methodology and artificial neural network2014 · 88 citations

KI fragen

Bookmark