Application of Back-Propagation Neural Network in the Post-Blast Re-Entry Time Prediction
Abstract
:1. Introduction
2. Model Process and Data Preparation
2.1. Model Construction
2.2. Database Generation
3. Methodology
3.1. BPNN Algorithm
3.2. Calibrating Empirical Formula
3.3. Performance Indicators for the Assessment of Models
4. Results and Discussion
4.1. Building the Architecture of the BPNN
4.2. Performance Comparison between BPNN and Formula
5. Algorithm Embedding
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Length/(m) | Gas/(L/kg) | Velocity/(m/s) | Limit/(ppm) | Time/(s) | |
1 | 469 | 40.47 | 1.31 | 38.52 | 246 |
2 | 921 | 39.53 | 2.57 | 31.90 | 140 |
3 | 1475 | 40.77 | 2.33 | 32.69 | 185 |
4 | 893 | 37.50 | 0.38 | 32.40 | 1040 |
5 | 393 | 40.27 | 1.34 | 24.62 | 246 |
6 | 243 | 38.16 | 2.37 | 37.60 | 121 |
7 | 256 | 40.40 | 3.25 | 33.73 | 90 |
8 | 439 | 40.02 | 2.10 | 41.43 | 152 |
9 | 324 | 40.61 | 0.69 | 29.08 | 448 |
10 | 347 | 41.58 | 1.77 | 44.34 | 166 |
11 | 510 | 38.91 | 2.31 | 31.86 | 145 |
12 | 474 | 36.20 | 3.79 | 33.98 | 86 |
13 | 954 | 36.09 | 3.50 | 38.44 | 107 |
14 | 1145 | 37.83 | 1.59 | 30.45 | 246 |
15 | 1381 | 36.61 | 1.99 | 40.52 | 201 |
16 | 967 | 39.21 | 1.72 | 34.15 | 221 |
17 | 385 | 41.72 | 3.21 | 36.36 | 94 |
18 | 601 | 38.99 | 1.03 | 36.23 | 336 |
19 | 977 | 36.35 | 1.92 | 30.20 | 200 |
20 | 1028 | 38.84 | 2.40 | 38.10 | 169 |
21 | 957 | 40.69 | 2.92 | 41.64 | 129 |
22 | 733 | 37.23 | 3.53 | 25.00 | 101 |
23 | 1459 | 41.48 | 3.54 | 49.79 | 120 |
24 | 307 | 36.69 | 0.77 | 31.24 | 401 |
25 | 363 | 41.33 | 0.79 | 39.60 | 377 |
26 | 535 | 37.85 | 3.66 | 46.26 | 89 |
27 | 1358 | 37.93 | 1.17 | 42.51 | 337 |
28 | 1490 | 40.42 | 2.49 | 34.57 | 174 |
29 | 891 | 39.11 | 3.62 | 35.44 | 109 |
30 | 1388 | 36.72 | 3.89 | 36.69 | 104 |
31 | 1287 | 38.94 | 1.65 | 39.18 | 270 |
32 | 865 | 41.51 | 1.08 | 30.82 | 354 |
33 | 1089 | 38.02 | 0.30 | 27.91 | 1419 |
34 | 271 | 41.53 | 0.42 | 37.10 | 679 |
35 | 799 | 38.20 | 3.26 | 26.70 | 121 |
36 | 1056 | 40.83 | 0.92 | 35.32 | 456 |
37 | 1218 | 39.50 | 1.45 | 24.92 | 289 |
38 | 1261 | 41.46 | 2.26 | 41.85 | 193 |
39 | 540 | 39.51 | 3.22 | 41.22 | 102 |
40 | 1160 | 36.17 | 0.55 | 42.26 | 729 |
41 | 454 | 41.63 | 2.36 | 45.01 | 131 |
42 | 875 | 39.01 | 0.47 | 47.88 | 723 |
43 | 1343 | 36.12 | 1.73 | 26.25 | 270 |
44 | 1414 | 41.35 | 1.38 | 38.31 | 299 |
45 | 606 | 40.44 | 3.77 | 26.08 | 92 |
46 | 1002 | 41.98 | 1.80 | 48.54 | 219 |
47 | 1449 | 37.53 | 2.19 | 47.50 | 193 |
48 | 266 | 39.80 | 2.53 | 45.38 | 115 |
49 | 302 | 41.93 | 3.31 | 25.87 | 95 |
50 | 1383 | 41.23 | 0.85 | 45.80 | 471 |
51 | 1033 | 40.59 | 1.70 | 37.31 | 240 |
52 | 1134 | 38.15 | 2.47 | 40.43 | 157 |
53 | 530 | 41.75 | 0.88 | 28.33 | 395 |
54 | 1495 | 37.79 | 3.83 | 28.24 | 114 |
55 | 1302 | 38.35 | 2.76 | 29.16 | 163 |
56 | 779 | 36.96 | 2.51 | 29.41 | 152 |
57 | 931 | 36.44 | 1.63 | 43.76 | 224 |
58 | 487 | 39.94 | 1.22 | 44.68 | 257 |
59 | 246 | 36.57 | 1.04 | 40.81 | 282 |
60 | 322 | 36.89 | 3.92 | 42.72 | 74 |
61 | 1114 | 36.37 | 3.69 | 27.95 | 120 |
62 | 373 | 39.85 | 3.13 | 30.66 | 98 |
63 | 1322 | 40.91 | 3.38 | 37.06 | 136 |
64 | 591 | 41.14 | 3.61 | 29.78 | 94 |
65 | 1363 | 39.36 | 2.08 | 36.44 | 228 |
66 | 467 | 37.42 | 1.89 | 24.50 | 182 |
67 | 771 | 36.16 | 1.30 | 27.20 | 290 |
68 | 317 | 41.21 | 2.79 | 39.35 | 107 |
69 | 738 | 39.38 | 1.75 | 47.09 | 205 |
70 | 809 | 37.48 | 1.40 | 28.99 | 254 |
71 | 916 | 37.14 | 1.46 | 34.98 | 244 |
72 | 1048 | 41.88 | 3.02 | 40.39 | 138 |
73 | 952 | 39.93 | 2.24 | 46.67 | 167 |
74 | 236 | 38.77 | 0.34 | 43.09 | 831 |
75 | 520 | 36.46 | 0.61 | 34.48 | 558 |
76 | 566 | 36.22 | 0.94 | 30.24 | 372 |
77 | 1332 | 38.68 | 1.91 | 44.88 | 242 |
78 | 1221 | 37.90 | 0.32 | 37.69 | 1332 |
79 | 946 | 37.95 | 2.94 | 45.17 | 126 |
80 | 759 | 40.64 | 2.03 | 30.86 | 183 |
81 | 936 | 38.12 | 1.19 | 36.65 | 307 |
82 | 1279 | 38.09 | 2.96 | 43.64 | 149 |
83 | 406 | 36.83 | 3.60 | 45.72 | 85 |
84 | 642 | 36.32 | 3.86 | 44.55 | 88 |
85 | 352 | 37.98 | 2.87 | 27.74 | 110 |
86 | 449 | 39.46 | 0.50 | 25.21 | 652 |
87 | 1211 | 38.54 | 3.55 | 35.19 | 117 |
88 | 1373 | 37.21 | 0.64 | 49.75 | 618 |
89 | 489 | 37.68 | 1.69 | 49.96 | 187 |
90 | 855 | 37.75 | 3.56 | 39.77 | 106 |
91 | 1231 | 41.73 | 2.56 | 47.25 | 166 |
92 | 225 | 41.01 | 2.23 | 27.08 | 133 |
93 | 1292 | 40.32 | 1.18 | 26.87 | 379 |
94 | 446 | 40.91 | 1.84 | 30.32 | 177 |
95 | 804 | 41.65 | 0.49 | 32.07 | 717 |
96 | 1424 | 38.79 | 3.72 | 30.41 | 111 |
97 | 860 | 38.52 | 1.52 | 25.46 | 250 |
98 | 1246 | 40.86 | 3.64 | 25.66 | 118 |
99 | 495 | 38.49 | 2.67 | 35.65 | 120 |
100 | 708 | 38.59 | 3.85 | 32.11 | 89 |
101 | 1180 | 39.75 | 3.03 | 49.13 | 134 |
102 | 1038 | 37.36 | 1.00 | 26.04 | 409 |
103 | 576 | 40.05 | 3.05 | 38.77 | 107 |
104 | 1297 | 36.15 | 2.32 | 35.23 | 194 |
105 | 1063 | 41.38 | 2.82 | 26.29 | 150 |
106 | 1068 | 37.06 | 3.63 | 31.65 | 117 |
107 | 814 | 39.68 | 1.16 | 34.36 | 309 |
108 | 794 | 37.80 | 2.38 | 43.72 | 146 |
109 | 1119 | 38.47 | 3.45 | 33.32 | 111 |
110 | 413 | 37.38 | 0.68 | 43.97 | 463 |
111 | 203 | 41.79 | 1.15 | 49.04 | 242 |
112 | 210 | 40.52 | 2.59 | 42.10 | 109 |
113 | 220 | 39.48 | 0.86 | 39.39 | 331 |
114 | 1444 | 41.80 | 0.39 | 24.58 | 1284 |
115 | 748 | 36.07 | 2.97 | 40.02 | 123 |
116 | 1378 | 39.56 | 1.78 | 32.32 | 269 |
117 | 291 | 36.30 | 1.82 | 37.94 | 164 |
118 | 784 | 39.28 | 3.78 | 49.33 | 91 |
119 | 1368 | 41.60 | 2.95 | 29.82 | 161 |
120 | 850 | 40.00 | 2.39 | 44.80 | 157 |
121 | 677 | 39.98 | 3.95 | 38.14 | 91 |
122 | 1282 | 36.47 | 3.99 | 48.92 | 111 |
123 | 934 | 41.57 | 2.06 | 25.12 | 202 |
124 | 703 | 36.62 | 1.33 | 32.90 | 283 |
125 | 690 | 40.24 | 3.67 | 36.56 | 90 |
126 | 1348 | 39.19 | 2.90 | 48.34 | 135 |
127 | 1470 | 39.83 | 1.06 | 27.33 | 404 |
128 | 251 | 38.96 | 3.58 | 28.37 | 84 |
129 | 873 | 40.39 | 1.61 | 42.60 | 241 |
130 | 429 | 36.25 | 3.07 | 28.74 | 107 |
131 | 1226 | 38.05 | 1.98 | 33.57 | 214 |
132 | 261 | 37.70 | 2.09 | 33.15 | 145 |
133 | 545 | 40.81 | 1.93 | 44.59 | 173 |
134 | 698 | 41.19 | 0.75 | 27.54 | 496 |
135 | 1454 | 39.65 | 2.63 | 42.47 | 161 |
136 | 1129 | 37.65 | 2.25 | 37.27 | 172 |
137 | 332 | 40.72 | 1.21 | 31.49 | 251 |
138 | 568 | 41.50 | 2.52 | 42.80 | 128 |
139 | 1124 | 40.20 | 1.11 | 44.38 | 345 |
140 | 926 | 40.99 | 3.70 | 46.63 | 98 |
141 | 880 | 41.16 | 2.13 | 37.73 | 183 |
142 | 1251 | 36.02 | 3.17 | 31.03 | 136 |
143 | 718 | 37.60 | 0.81 | 35.02 | 430 |
144 | 1178 | 41.13 | 0.46 | 43.84 | 883 |
145 | 1241 | 39.14 | 0.93 | 40.18 | 461 |
146 | 444 | 37.78 | 3.23 | 36.48 | 100 |
147 | 1327 | 37.31 | 1.27 | 32.94 | 363 |
148 | 357 | 39.35 | 3.52 | 33.11 | 87 |
149 | 629 | 40.09 | 0.82 | 33.24 | 404 |
150 | 1256 | 38.44 | 1.09 | 46.88 | 397 |
151 | 1434 | 36.40 | 1.10 | 38.93 | 378 |
152 | 682 | 40.68 | 2.98 | 24.08 | 122 |
153 | 657 | 36.49 | 2.28 | 25.25 | 153 |
154 | 652 | 40.35 | 0.62 | 40.60 | 555 |
155 | 1340 | 38.24 | 0.99 | 31.36 | 468 |
156 | 1353 | 40.62 | 3.48 | 43.30 | 113 |
157 | 886 | 36.54 | 2.48 | 24.79 | 159 |
158 | 1155 | 40.74 | 3.28 | 47.30 | 121 |
159 | 434 | 38.86 | 0.96 | 46.46 | 326 |
160 | 548 | 38.39 | 3.75 | 25.96 | 90 |
161 | 789 | 40.37 | 1.02 | 48.75 | 340 |
162 | 1170 | 40.46 | 2.75 | 29.28 | 146 |
163 | 992 | 37.41 | 2.74 | 38.98 | 142 |
164 | 688 | 36.67 | 1.86 | 48.96 | 178 |
165 | 1312 | 37.43 | 1.79 | 41.01 | 254 |
166 | 1480 | 36.52 | 0.45 | 31.70 | 966 |
167 | 1150 | 39.43 | 1.26 | 48.29 | 314 |
168 | 378 | 40.84 | 0.26 | 48.50 | 1113 |
169 | 459 | 37.28 | 2.71 | 39.97 | 116 |
170 | 609 | 39.57 | 0.76 | 45.92 | 417 |
171 | 550 | 36.02 | 2.61 | 37.48 | 129 |
172 | 1139 | 41.68 | 3.84 | 39.56 | 102 |
173 | 812 | 41.28 | 2.29 | 47.80 | 155 |
174 | 555 | 39.16 | 0.27 | 32.53 | 1254 |
175 | 710 | 37.05 | 0.28 | 41.56 | 1213 |
176 | 337 | 36.10 | 2.02 | 46.21 | 147 |
177 | 743 | 41.06 | 0.95 | 42.05 | 381 |
178 | 835 | 40.17 | 2.69 | 25.62 | 137 |
179 | 1236 | 37.04 | 1.37 | 45.22 | 312 |
180 | 662 | 38.10 | 2.86 | 30.61 | 123 |
181 | 1216 | 40.22 | 3.08 | 40.64 | 136 |
182 | 1317 | 39.41 | 3.81 | 44.18 | 120 |
183 | 1195 | 38.81 | 0.63 | 26.91 | 649 |
184 | 723 | 39.88 | 1.94 | 28.95 | 180 |
185 | 627 | 37.26 | 0.48 | 36.27 | 687 |
186 | 284 | 37.57 | 3.14 | 41.76 | 92 |
187 | 368 | 37.09 | 1.96 | 38.73 | 154 |
188 | 941 | 40.30 | 3.97 | 32.74 | 93 |
189 | 479 | 38.32 | 3.32 | 47.67 | 93 |
190 | 987 | 40.10 | 0.72 | 35.81 | 539 |
191 | 1462 | 39.28 | 0.53 | 37.40 | 797 |
192 | 342 | 38.07 | 0.60 | 49.38 | 479 |
193 | 286 | 40.12 | 3.87 | 47.05 | 75 |
194 | 1175 | 37.33 | 3.46 | 29.20 | 116 |
195 | 1109 | 41.28 | 1.64 | 28.53 | 270 |
196 | 223 | 36.39 | 2.68 | 32.20 | 109 |
197 | 281 | 38.67 | 2.70 | 33.36 | 113 |
198 | 616 | 38.30 | 1.29 | 43.14 | 250 |
199 | 972 | 40.89 | 1.24 | 24.83 | 307 |
200 | 728 | 41.56 | 2.85 | 37.52 | 124 |
201 | 1404 | 37.58 | 2.84 | 33.94 | 143 |
202 | 1185 | 41.85 | 0.98 | 35.86 | 414 |
203 | 1307 | 40.49 | 0.52 | 46.05 | 865 |
204 | 241 | 41.11 | 1.47 | 45.84 | 191 |
205 | 754 | 38.25 | 0.70 | 39.14 | 527 |
206 | 528 | 37.13 | 2.22 | 33.44 | 157 |
207 | 621 | 41.95 | 1.87 | 34.77 | 192 |
208 | 693 | 39.09 | 2.80 | 43.93 | 119 |
209 | 1023 | 37.19 | 2.05 | 41.06 | 197 |
210 | 901 | 36.05 | 0.91 | 49.17 | 387 |
211 | 1015 | 36.24 | 1.53 | 46.96 | 262 |
212 | 1198 | 37.72 | 1.07 | 46.76 | 385 |
213 | 1190 | 36.84 | 2.15 | 27.70 | 190 |
214 | 312 | 39.60 | 1.88 | 40.22 | 155 |
215 | 1409 | 38.64 | 0.73 | 41.26 | 560 |
216 | 1165 | 39.31 | 2.34 | 24.17 | 171 |
217 | 418 | 39.73 | 1.49 | 36.85 | 214 |
218 | 505 | 36.74 | 1.14 | 26.50 | 290 |
219 | 830 | 38.74 | 2.21 | 36.90 | 166 |
220 | 647 | 38.89 | 3.39 | 45.63 | 101 |
221 | 1360 | 41.05 | 2.43 | 28.04 | 195 |
222 | 764 | 37.35 | 2.45 | 48.71 | 136 |
223 | 388 | 38.02 | 3.68 | 42.68 | 83 |
224 | 1073 | 39.04 | 0.83 | 29.62 | 513 |
225 | 464 | 39.26 | 1.55 | 41.47 | 205 |
226 | 304 | 39.05 | 1.35 | 48.84 | 217 |
227 | 1200 | 40.02 | 1.54 | 32.28 | 268 |
228 | 1393 | 39.06 | 3.09 | 25.41 | 157 |
229 | 825 | 36.77 | 3.40 | 37.89 | 107 |
230 | 1058 | 39.90 | 1.39 | 42.89 | 302 |
231 | 1485 | 38.17 | 1.62 | 46.42 | 268 |
232 | 649 | 37.94 | 1.76 | 39.48 | 195 |
233 | 769 | 39.78 | 0.40 | 41.68 | 830 |
234 | 1271 | 39.95 | 0.57 | 29.57 | 774 |
235 | 713 | 41.36 | 3.15 | 46.84 | 110 |
236 | 1421 | 40.16 | 3.44 | 48.00 | 120 |
237 | 327 | 39.23 | 2.99 | 35.40 | 100 |
238 | 962 | 36.94 | 0.58 | 28.78 | 653 |
239 | 853 | 39.79 | 3.29 | 38.64 | 115 |
240 | 383 | 36.59 | 2.78 | 47.71 | 108 |
241 | 1053 | 37.56 | 0.71 | 47.92 | 504 |
242 | 296 | 38.62 | 0.80 | 24.37 | 400 |
243 | 581 | 37.73 | 0.41 | 26.45 | 872 |
244 | 586 | 39.70 | 2.44 | 24.42 | 150 |
245 | 974 | 38.61 | 2.83 | 49.88 | 135 |
246 | 911 | 41.70 | 0.29 | 43.55 | 1209 |
247 | 820 | 41.83 | 3.74 | 40.85 | 96 |
248 | 525 | 38.00 | 1.32 | 34.40 | 261 |
249 | 870 | 36.81 | 3.01 | 34.19 | 128 |
250 | 1094 | 41.78 | 2.16 | 31.28 | 201 |
251 | 896 | 40.57 | 3.18 | 27.29 | 125 |
252 | 423 | 41.04 | 3.51 | 34.82 | 92 |
253 | 1007 | 36.68 | 0.84 | 43.51 | 472 |
254 | 365 | 39.13 | 2.60 | 26.16 | 121 |
255 | 398 | 37.88 | 0.87 | 29.99 | 363 |
256 | 1013 | 39.33 | 2.93 | 28.16 | 136 |
257 | 1104 | 39.63 | 0.37 | 34.61 | 1016 |
258 | 1137 | 37.28 | 3.37 | 27.00 | 135 |
259 | 632 | 38.69 | 1.85 | 28.12 | 198 |
260 | 1266 | 37.63 | 3.43 | 24.21 | 127 |
261 | 637 | 40.94 | 2.72 | 49.58 | 123 |
262 | 1299 | 41.94 | 3.90 | 34.28 | 115 |
263 | 611 | 37.46 | 3.33 | 31.45 | 105 |
264 | 774 | 40.79 | 1.57 | 35.61 | 241 |
265 | 1419 | 37.11 | 2.55 | 25.04 | 194 |
266 | 1035 | 39.72 | 2.14 | 31.16 | 191 |
267 | 1398 | 40.07 | 1.90 | 28.58 | 256 |
268 | 982 | 38.72 | 3.35 | 41.89 | 115 |
269 | 276 | 36.99 | 1.56 | 25.83 | 197 |
270 | 845 | 38.46 | 1.68 | 39.68 | 222 |
271 | 205 | 38.42 | 1.42 | 29.37 | 208 |
272 | 500 | 41.43 | 3.93 | 27.49 | 83 |
273 | 1338 | 40.67 | 0.56 | 38.56 | 834 |
274 | 731 | 38.83 | 3.06 | 30.12 | 116 |
275 | 561 | 40.54 | 1.41 | 45.59 | 225 |
276 | 667 | 41.41 | 1.67 | 33.78 | 212 |
277 | 1205 | 36.27 | 2.41 | 42.93 | 172 |
278 | 484 | 40.15 | 0.33 | 30.03 | 1030 |
279 | 906 | 38.40 | 2.17 | 44.13 | 162 |
280 | 215 | 37.51 | 3.76 | 36.02 | 71 |
281 | 1096 | 38.91 | 3.98 | 40.72 | 94 |
282 | 1079 | 40.25 | 2.00 | 49.54 | 184 |
283 | 840 | 36.42 | 0.35 | 44.97 | 1062 |
284 | 1018 | 41.09 | 0.65 | 33.53 | 614 |
285 | 515 | 41.31 | 3.41 | 43.34 | 91 |
286 | 1084 | 36.64 | 3.10 | 36.06 | 139 |
287 | 1099 | 36.79 | 2.64 | 46.01 | 142 |
288 | 1464 | 37.01 | 3.30 | 44.76 | 129 |
289 | 672 | 36.91 | 1.23 | 47.46 | 290 |
290 | 1277 | 41.26 | 2.62 | 31.07 | 168 |
291 | 403 | 38.22 | 2.01 | 27.12 | 160 |
292 | 1439 | 38.37 | 3.16 | 38.35 | 133 |
293 | 571 | 38.57 | 2.11 | 48.09 | 154 |
294 | 1259 | 36.91 | 2.91 | 35.52 | 150 |
295 | 408 | 41.90 | 2.46 | 32.49 | 125 |
296 | 230 | 37.16 | 3.20 | 48.13 | 89 |
297 | 997 | 39.58 | 3.91 | 26.66 | 100 |
298 | 1043 | 38.27 | 3.49 | 45.42 | 118 |
299 | 1429 | 40.96 | 1.44 | 39.81 | 288 |
300 | 596 | 36.86 | 1.50 | 42.30 | 228 |
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TWA/ppm | STEL/ppm | |
---|---|---|
ASM-2 | 50 | 100 |
NIOSH REL | 35 | 200 |
NOHSC | 30 | 200 |
OSHA PEL | 35 | 200 |
CHINA | 16 | 24 |
Reference | Equation | Way |
---|---|---|
[4] | Calibration | |
[7] | Calibration | |
[7] | Calibration | |
[9] | Fitting | |
[9] | Fitting | |
[10] | Fitting | |
[11] | Derivation | |
[11] | Derivation | |
[15] | Calibration |
Model | Neurons | RMSE | R2 | ||
---|---|---|---|---|---|
Training | Testing | Training | Testing | ||
1 | 2 | 16.0196 | 21.9249 | 0.9959 | 0.9922 |
2 | 3 | 55.9012 | 37.0202 | 0.9502 | 0.9776 |
3 | 4 | 72.4646 | 60.601 | 0.9163 | 0.9401 |
4 | 5 | 61.6996 | 50.5617 | 0.9393 | 0.9583 |
5 | 6 | 12.6171 | 21.3421 | 0.9975 | 0.9926 |
6 | 7 | 14.3551 | 21.026 | 0.9967 | 0.9928 |
7 | 8 | 14.7677 | 21.4577 | 0.9965 | 0.9925 |
8 | 9 | 14.2703 | 22.0516 | 0.9968 | 0.9921 |
9 | 10 | 13.1419 | 21.6439 | 0.9973 | 0.9924 |
Indicators | Training | Testing | ||
---|---|---|---|---|
Empirical | BPNN | Empirical | BPNN | |
RMSE | 61.81 | 12.61 | 76.89 | 21.34 |
MAE | 38.34 | 7.66 | 42.06 | 10.78 |
R2 | 0.94 | 0.99 | 0.90 | 0.99 |
SSE | 798352 | 33429 | 526147 | 40934 |
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Zhang, J.; Li, C.; Zhang, T. Application of Back-Propagation Neural Network in the Post-Blast Re-Entry Time Prediction. Knowledge 2023, 3, 128-148. https://doi.org/10.3390/knowledge3020010
Zhang J, Li C, Zhang T. Application of Back-Propagation Neural Network in the Post-Blast Re-Entry Time Prediction. Knowledge. 2023; 3(2):128-148. https://doi.org/10.3390/knowledge3020010
Chicago/Turabian StyleZhang, Jinrui, Chuanqi Li, and Tingting Zhang. 2023. "Application of Back-Propagation Neural Network in the Post-Blast Re-Entry Time Prediction" Knowledge 3, no. 2: 128-148. https://doi.org/10.3390/knowledge3020010