Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM) Approach for Modelling the Optimization of Chromium (VI) Reduction by Newly Isolated<i> Acinetobacter radioresistens</i> Strain NS-MIE from Agricultural Soil

<p>Optical density of<i> A. radioresistens</i> strain NS-MIE at different concentrations of hexavalent chromium.</p>

BioMed Research International

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Figure 6

Figure 6: Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM) Approach for Modelling the Optimization of Chromium (VI) Reduction by Newly Isolated<i> Acinetobacter radioresistens</i> Strain NS-MIE from Agricultural Soil 

Figure 6 | Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM) Approach for Modelling the Optimization of Chromium (VI) Reduction by Newly Isolated Acinetobacter radioresistens Strain NS-MIE from Agricultural Soil 