Computational Modeling of Biosynthesized Gold Nanoparticles in Black Camellia sinensis Leaf Extract

Table 1

Comparison of proposed method with other ANN training algorithm methods (the results have been run over 50 times).

Training algorithm		Error of MSE for train data set	Error of MSE test data set	Error of MSE for all data set	train data set	test data set	all data set
BBO	Mean	0.02788	0.13976	0.050253	0.94158	0.8502	0.90211
	Std.	0.00994	0.084918	0.02284	0.030358	0.095858	0.05488
IBBO	Mean	0.0168	0.06842	0.027123	0.9655	0.82075	0.9426
	Std.	0.00870	0.04921	0.013165	0.01536	0.16422	0.02109
LM	Mean	0.82218	0.73313	0.80437	0.20929	0.071544	0.19152
	Std.	0.45563	0.50258	0.43994	0.55242	0.59973	0.53191
BR	Mean	0.89932	0.91367	0.90219	0.08041	0.16773	0.08368
	Std.	0.54795	0.61153	0.53461	0.6546	0.55121	0.62575
BFGS	Mean	0.84558	0.66035	0.80853	0.00926	−0.10722	−0.01068
	Std.	0.45243	0.45886	0.45193	0.59425	0.66829	0.60458
GDA	Mean	0.6908	0.75501	0.70364	0.08736	−0.03519	0.06249
	Std.	0.44392	0.5596	0.45799	0.62295	0.64031	0.619
FCG	Mean	0.68511	0.83815	0.71572	0.15577	0.22267	0.19553
	Std.	0.48889	0.73824	0.53275	0.56779	0.59573	0.5627