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

Table 11

Comparative error analysis of RSM and ANN models.

Error		Model
		RSM	ANN
Root mean square error	RMSE	0.6781	0.302
Correlation coefficients	R^2	0.9974	0.9991
Standard error of prediction	SEP (%)	2.1900	0.3300
Relative percent deviation	RPD (%)	1.9984	2.5700