Modelling of n-Hexadecane bioremediation from soil by slurry bioreactors using artificial neural network method.

ABSTRACT: Diesel oil is known to be one of the major petroleum products that can pollute water and soil. Soil pollution caused by petroleum hydrocarbons has substantially impacted the environment, especially in the Middle East. In this study, modeling and optimization of hexadecane removal from soil was performed using two pure cultures of Acinetobacter and Acromobacter and consortium culture of both bacterial species using artificial neural network (ANN) method. Then the best ANN structure was proposed based on mean square error (MSE) as well as correlation coefficient (R) for pure cultures of Acinetobacter and Acromobacter as well as their consortium. The results showed that the correlations between the actual data and the data predicted by ANN (R2) in Acromobacter, Acinetobacter and consortium of

SUBMITTER: Morovati R 

PROVIDER: S-EPMC9669037 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature