Comparison of Two Quantitative Analysis Techniques to Predict the Evaluation of Product Form Design

Table 4

RMSE of NN prediction models for automobile profile training dataset.

Number of training epochs	NN-Arith.	NN-Geom.	NN-Sum
	I: 92 neurons; H: 49 neurons; O: 6 neurons	I: 92 neurons; H: 23 neurons; O: 6 neurons	I: 92 neurons; H: 98 neurons; O: 6 neurons
1000	0.1028	0.1031	0.1069
2000	0.0956	0.0970	0.0964
5000	0.0846	0.0871	0.0872
10,000	0.0775	0.0787	0.0791
20,000	0.0672	0.0685	0.0684
30,000	0.0620	0.0638	0.0643
40,000	0.0588	0.0606	0.0610
50,000	0.0576	0.0599	0.0603
60,000	0.0567	0.0587	0.0592
70,000	0.0558	0.0577	0.0584
80,000	0.0553	0.0570	0.0579
90,000	0.0550	0.0570	0.0577

“I,” “H,” and “O” indicate the input, hidden, and output layer, respectively.