Phytoextraction capability of Azolla pinnata in the removal of rhodamine B from aqueous solution: artificial neural network and random forests approaches

Phytoextraction capability of Azolla pinnata in the removal of rhodamine B from aqueous solution: artificial neural network and random forests approaches

Abstract This study used live Azolla pinnata (AP) to remediate rhodamine B (RB) from aqueous solutions via the phytoextraction method, and machine learning algorithms such as artificial neural networks and random forests were used as predictive models. The pH was found to have a major influence on t...

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Bibliographic Details
Main Authors: Muhammad Raziq Rahimi Kooh, Muhammad Khairud Dahri, Linda B. L. Lim, Lee Hoon Lim, Sze Ling Lee
Format: Article
Language:English
Published: SpringerOpen 2019-05-01
Series:Applied Water Science
Subjects:
Phytoextraction
Rhodamine B
Artificial neural network
Random forests
Machine learning algorithms
Azolla pinnata
Online Access:http://link.springer.com/article/10.1007/s13201-019-0960-6

Internet

http://link.springer.com/article/10.1007/s13201-019-0960-6

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