Research on Credit Evaluation of Financial Enterprises Based on the Genetic Backpropagation Neural Network

Table 3

Connection weights of the input layer and hidden layer after training.

Input layer	Hidden layer
	1	2	3	4	5	6
1	−0.5349	0.6554	0.3255	0.091	−1.0189	1.1820
2	0.8526	−0.4313	1.2015	−1.0425	0.4017	−0.1709
3	1.1856	1.1660	0.2807	−0.4031	−02354	1.126
4	1.1660	0.2807	−0.3892	0.556	−1.0425	0.8050
5	−0.1402	−0.3642	0.9511	1.2881	0.0406	−0.3059
6	0.1369	0.8786	−1.171	−0.30559	0.2082	0.8186
7	0.5556	0.9290	1.0406	0.1569	1.1369	−0.8414
8	−0.5714	1.2881	0.7082	−0.3678	−0.9727	−0.8135
9	−0.4274	0.4695	0.5004	0.7118	0.9667	1.2990
10	−0.9711	0.1421	1.3295	−0.2142	0.0731	1.0525
11	1.2646	−0.7481	0.774	−0.3154	−0.0107	−0.8469
12	1.0484	−0.9704	1.668	−0.5349	1.2822	−0.4742
13	1.1615	−0.8296	−0.5125	−1.0189	1.4454	0.0091
14	0.6554	0.3255	−0.4586	0.6942	0.8477	−0.4313
15	−0.1584	−0.8720	1.820	0.6670	0.8526	0.8651
16	−0.6971	0.2784	0.5465	−0.6697	0.4232	0.5555
17	0.0552	1.3068	−0.3870	0.3055	−0.6873	0.8310
18	0.4686	0.7038	−0.6208	−0.5677	0.4911	−0.2349