6_8pyb.txt

BP神经网络,可以进行任意发酵过程建模,包括初始化,训练与测试,

0, 6.63, 100, 0, 4.89, 0
4, 6.63, 99, 0.05, 4.18, 0
8, 6.63, 81.7, 0.183, 4.163, 0
12, 6.63, 64.3, 0.317, 4.147, 0
16, 6.63, 47, 0.45, 4.13, 0
20, 6.69, 5, 1.16, 4.03, 0
24, 6.19, 2, 1.29, 3.85, 0
28, 5.31, 0, 1.46, 3.83, 0
32, 4.957, 0, 1.303, 3.83, 0
36, 4.25, 0, 0.99, 3.83, 0
40, 4.31, 5, 0.75, 3.8, 0.18
44, 4.31, 2, 0.31, 3.78, 0.36
48, 4.38, 0, 1.25, 3.75, 0.31
52, 4.44, 0, 1.74, 3.7, 0.26
56, 4.47, 0, 1.78, 3.69, 0.24
60, 4.52, 0, 1.93, 3.67, 0.21
64, 4.56, 0, 2.08, 3.65, 0.18
68, 4.69, 3, 2.34, 3.58, 0.18
72, 4.81, 2, 2.6, 3.5, 0.15
0, 6.2, 100, 0, 4.92, 0.23
4, 6.19, 100, 0, 4.89, 0.35
8, 6.19, 97, 0, 4.82, 0.65
12, 6.13, 97, 0, 4.75, 0.82
16, 6.22, 87, 0.17, 4.64, 0.865
20, 6.31, 77, 0.34, 4.53, 0.91
24, 5.13, 65, 1.25, 4.15, 0.91
28, 3, 79, 1.89, 4.1, 0.93
32, 2.69, 82, 2.06, 4, 0.94
36, 2.63, 87, 2.15, 4, 0.96
40, 2.595, 86, 2.195, 4, 0.985
44, 2.56, 85, 2.24, 4, 1.01
48, 2.5, 81, 1.81, 3.85, 1.03
52, 2.5, 76, 2.26, 3.8, 1.1
56, 2.31, 55, 1.92, 3.75, 1.16
60, 2.27, 39.67, 1.947, 3.47, 1.213
64, 2.23, 24.33, 1.974, 3.18, 1.267
68, 2.19, 9, 2, 2.9, 1.32
72, 2.13, 7, 2.48, 2.85, 1.48
0, 6.7, 100, 0.77, 4.89, 0
4, 6.665, 100, 0.77, 4.57, 0
8, 6.63, 100, 0.77, 4.25, 0
12, 6.63, 96, 0.88, 3.9, 0.34
16, 6.63, 85, 1.16, 3.85, 0.45
20, 6.56, 6.9, 2.6, 3.87, 0.47
24, 6.19, 64, 2.55, 3.7, 0.53
28, 4.69, 75.5, 2.625, 3.66, 0.61
32, 3.19, 87, 2.7, 3.62, 0.69
36, 3, 88, 2.79, 3.55, 0.75
40, 3, 82, 3.17, 3.45, 0.75
44, 3, 77, 3.09, 3.3, 0.84
48, 3, 64, 2.95, 3.25, 0.89
52, 3, 59.5, 3.03, 3.19, 0.815
56, 3, 55, 3.11, 3.13, 0.74
60, 3, 47, 3.64, 2.65, 0.65
64, 3, 40, 3.81, 2.1, 0.65
68, 3, 5, 4.61, 1.95, 0.64
72, 3.09, 4, 3.52, 1.95, 0.63
0, 6.63, 100, 0.34, 4.94, 0
4, 6.563, 95.5, 0.49, 4.835, 0.12
8, 6.5, 91, 0.64, 4.73, 0.24
12, 6.63, 87, 0.6, 4.31, 0.57
16, 6.38, 84, 1.48, 4.05, 0.59
20, 5.25, 86, 1.65, 3.95, 0.85
24, 4, 75, 2.59, 3.7, 0.9
28, 4.03, 52, 4.065, 3.565, 0.97
32, 4.06, 29, 5.54, 3.43, 1.04
36, 4, 16, 4.78, 2.85, 1.17
40, 4.06, 12, 7.18, 2.55, 1.54
44, 4, 6, 8.62, 1.85, 1.83
48, 4.06, 17, 8.5, 1.83, 1.94
52, 4.06, 16, 8.92, 1.39, 2.125
56, 4.06, 15, 9.33, 0.95, 2.31
60, 4, 15, 8.17, 0.68, 2.45
64, 4, 28, 7.96, 0.4, 2.9
68, 4, 21, 7.65, 0.2, 2.95
72, 4, 20, 7.42, 0.05, 2.94
0, 6.69, 100, 0, 4.9, 0
4, 6.75, 100, 0.04, 4.81, 0.11
8, 6.75, 100, 1.27, 4.25, 0.28
12, 6.75, 98, 1.51, 4.08, 0.31
16, 6.73, 88.3, 1.447, 3.87, 0.323
20, 6.71, 78.7, 1.383, 3.66, 0.337
24, 6.69, 69, 1.32, 3.45, 0.35
28, 5.25, 66, 1.49, 3.3, 0.43
32, 5.1875, 65, 1.6225, 3.175, 0.505
36, 5.125, 64, 1.755, 3.05, 0.58
40, 5.0625, 63, 1.8875, 2.925, 0.655
44, 5, 62, 2.02, 2.8, 0.73
48, 5, 69, 2.98, 2.6, 1.09
52, 5, 51, 4.23, 2.45, 1.29
56, 5, 33, 3.95, 2.3, 1.52
60, 5, 24, 5.82, 1.85, 1.54
64, 5, 14.5, 7.53, 1.55, 1.575
68, 5, 5, 8.24, 1.25, 1.61
72, 5, 9, 8.9, 1, 1.42
0, 6.75, 100, 0, 4.43, 0.5452
4, 6.81, 93, 0, 4.55, 0.6303
8, 6.94, 77, 0, 4.325, 0.4734
12, 6.5, 53, 0.38, 4.225, 0.5159
16, 5.94, 81, 1.21, 4.025, 0.6117
20, 4.81, 50, 1.36, 3.725, 0.4547
24, 4.31, 30, 3.05, 3.43, 0.5984
32, 4.31, 5, 3.2, 2.88, 0.699
36, 4.31, 2, 5.65, 2.45, 0.8616
40, 4.31, 1, 4.69, 2.13, 0.8324
44, 4.31, 1, 5.92, 2.05, 0.8776
48, 4.31, 2, 4.36, 1.7, 0.851
52, 4.31, 2, 5.33, 1.45, 0.9466
56, 4.31, 3, 7.03, 0.8, 0.9973
60, 4.31, 0, 7.4, 0.45, 1.0026
64, 4.31, 0, 7.25, 0.28, 1.0319
68, 5.94, 40, 6.4, 0.15, 0.8829
72, 7.56, 52, 7.87, 0.1, 0.5452