Machine Learning Modeling of Aerobic Biodegradation for Azo Dyes and Hexavalent Chromium

Machine Learning Modeling of Aerobic Biodegradation for Azo Dyes and Hexavalent Chromium

The present study emphasizes the efficacy of a biosurfactant-producing bacterial strain <i>Klebsiella</i> sp. KOD36 in biodegradation of azo dyes and hexavalent chromium individually and in a simultaneous system. The bacterial strain has exhibited a considerable potential for biodegradat...

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Bibliographic Details
Main Authors: Zulfiqar Ahmad, Hua Zhong, Amir Mosavi, Mehreen Sadiq, Hira Saleem, Azeem Khalid, Shahid Mahmood, Narjes Nabipour
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Mathematics
Subjects:
biodegradation
chromium
azo dyes
prediction
SVR-FOA
Online Access:https://www.mdpi.com/2227-7390/8/6/913

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