1 1 34.9983 0.8400 100.0 449.44 555.32 1358.61 1137.23 5.48 8.00 194.64 2222.65 8341.91 1.02 42.02 183.06 2387.72 8048.56 9.3461 0.02 334 2223 100.00 14.73 8.8071
1 2 41.9982 0.8408 100.0 445.00 549.90 1353.22 1125.78 3.91 5.71 138.51 2211.57 8303.96 1.02 42.20 130.42 2387.66 8072.30 9.3774 0.02 330 2212 100.00 10.41 6.2665
1 3 24.9988 0.6218 60.0 462.54 537.31 1256.76 1047.45 7.05 9.02 175.71 1915.11 8001.42 0.94 36.69 164.22 2028.03 7864.87 10.8941 0.02 309 1915 84.93 14.08 8.6723
1 4 42.0077 0.8416 100.0 445.00 549.51 1354.03 1126.38 3.91 5.71 138.46 2211.58 8303.96 1.02 41.96 130.72 2387.61 8068.66 9.3528 0.02 329 2212 100.00 10.59 6.4701
1 5 25.0005 0.6203 60.0 462.54 537.07 1257.71 1047.93 7.05 9.03 175.05 1915.10 7993.23 0.94 36.89 164.31 2028.00 7861.23 10.8963 0.02 309 1915 84.93 14.13 8.5286
1 6 25.0045 0.6205 60.0 462.54 537.02 1266.38 1048.72 7.05 9.03 175.17 1915.15 7996.10 0.94 36.78 164.27 2028.01 7868.87 10.8912 0.02 306 1915 84.93 14.28 8.5590
1 7 42.0043 0.8409 100.0 445.00 549.74 1347.45 1127.19 3.91 5.71 138.71 2211.62 8307.75 1.02 42.19 130.49 2387.69 8075.54 9.3753 0.02 330 2212 100.00 10.62 6.4227
1 8 20.0020 0.7002 100.0 491.19 607.44 1481.69 1252.36 9.35 13.65 334.41 2323.87 8709.12 1.08 44.27 315.11 2387.99 8049.26 9.2369 0.02 365 2324 100.00 24.33 14.7989
1 9 41.9995 0.8407 100.0 445.00 549.33 1348.23 1127.45 3.91 5.71 138.06 2211.61 8312.33 1.02 42.30 130.97 2387.62 8065.78 9.3878 0.02 331 2212 100.00 10.69 6.3802
1 10 42.0011 0.8400 100.0 445.00 549.33 1356.40 1127.11 3.91 5.71 138.70 2211.56 8302.31 1.02 42.02 130.50 2387.62 8069.11 9.3957 0.02 329 2212 100.00 10.57 6.2847
1 11 42.0029 0.8400 100.0 445.00 549.81 1352.72 1126.23 3.91 5.71 137.81 2211.59 8301.22 1.02 42.05 130.41 2387.64 8076.44 9.3871 0.02 331 2212 100.00 10.51 6.3394
1 12 0.0015 0.0010 100.0 518.67 642.70 1585.52 1402.63 14.62 21.61 553.93 2388.12 9038.84 1.30 47.34 521.29 2388.16 8121.09 8.3892 0.03 393 2388 100.00 39.04 23.2694
1 13 20.0003 0.7000 100.0 491.19 607.67 1488.74 1256.10 9.35 13.65 335.33 2323.87 8710.39 1.08 44.43 314.77 2388.04 8048.52 9.1968 0.02 365 2324 100.00 24.40 14.7202
1 14 42.0020 0.8407 100.0 445.00 549.47 1352.69 1121.20 3.91 5.71 138.60 2211.59 8312.22 1.02 42.11 130.60 2387.69 8070.37 9.3905 0.02 330 2212 100.00 10.69 6.3230
1 15 10.0038 0.2513 100.0 489.05 604.57 1501.72 1305.97 10.52 15.49 395.21 2318.87 8765.10 1.26 45.49 372.03 2388.14 8118.56 8.6079 0.03 369 2319 100.00 28.54 17.1272
1 16 35.0053 0.8419 100.0 449.44 555.56 1362.41 1126.95 5.48 8.00 194.44 2222.76 8336.74 1.02 41.74 182.78 2387.76 8053.94 9.3232 0.02 332 2223 100.00 14.96 8.9446
1 17 25.0077 0.6217 60.0 462.54 536.25 1260.07 1053.00 7.05 9.02 175.21 1915.12 8005.82 0.94 36.73 164.53 2028.03 7857.51 10.8616 0.02 307 1915 84.93 14.07 8.5935
1 18 34.9996 0.8404 100.0 449.44 555.45 1365.15 1135.62 5.48 8.00 193.77 2222.70 8336.57 1.02 41.98 182.72 2387.72 8052.73 9.3419 0.02 334 2223 100.00 14.99 8.9676
1 19 42.0018 0.8400 100.0 445.00 549.07 1349.47 1134.82 3.91 5.71 138.72 2211.59 8300.02 1.02 42.02 130.42 2387.63 8070.70 9.3798 0.02 332 2212 100.00 10.49 6.4195
1 20 20.0020 0.7015 100.0 491.19 607.90 1482.44 1255.75 9.35 13.66 334.43 2323.94 8708.90 1.08 44.43 314.85 2388.08 8047.01 9.2623 0.02 366 2324 100.00 24.46 14.6601
1 21 42.0028 0.8403 100.0 445.00 549.68 1350.29 1130.26 3.91 5.72 137.93 2211.59 8303.44 1.02 42.28 129.98 2387.62 8071.57 9.3824 0.02 331 2212 100.00 10.56 6.3982
1 22 42.0043 0.8419 100.0 445.00 549.58 1352.73 1129.43 3.91 5.71 138.79 2211.58 8300.20 1.02 42.01 130.79 2387.72 8069.93 9.3587 0.02 330 2212 100.00 10.58 6.4241
1 23 41.9987 0.8416 100.0 445.00 549.44 1347.47 1126.30 3.91 5.71 138.55 2211.59 8300.28 1.02 41.97 130.48 2387.76 8070.05 9.3398 0.02 331 2212 100.00 10.56 6.4308
1 24 42.0011 0.8400 100.0 445.00 550.18 1352.82 1127.92 3.91 5.72 138.21 2211.59 8308.75 1.02 42.03 130.17 2387.64 8069.53 9.3807 0.02 332 2212 100.00 10.48 6.3598
1 25 42.0063 0.8400 100.0 445.00 549.42 1350.32 1122.44 3.91 5.72 139.02 2211.59 8306.69 1.02 42.25 130.73 2387.64 8066.98 9.3480 0.02 332 2212 100.00 10.55 6.4923
1 26 42.0001 0.8402 100.0 445.00 549.36 1357.42 1125.15 3.91 5.71 138.68 2211.71 8308.90 1.02 42.16 130.42 2387.67 8072.18 9.3704 0.02 331 2212 100.00 10.62 6.3448
1 27 25.0058 0.6206 60.0 462.54 537.01 1263.21 1048.03 7.05 9.02 176.05 1915.13 7998.23 0.94 36.77 164.30 2027.94 7859.12 10.9077 0.02 308 1915 84.93 14.27 8.6005
1 28 0.0022 0.0000 100.0 518.67 643.04 1589.28 1403.50 14.62 21.61 554.08 2388.13 9037.52 1.30 47.65 521.17 2388.14 8122.45 8.4871 0.03 392 2388 100.00 38.93 23.2184
1 29 0.0007 0.0000 100.0 518.67 642.48 1599.79 1415.68 14.62 21.61 553.49 2388.10 9039.24 1.30 47.33 521.33 2388.07 8121.25 8.4545 0.03 390 2388 100.00 38.73 23.1713
1 30 20.0060 0.7011 100.0 491.19 607.78 1485.69 1244.78 9.35 13.65 334.53 2323.89 8713.70 1.08 44.35 314.92 2388.06 8043.80 9.2372 0.02 365 2324 100.00 24.43 14.6832
1 31 10.0050 0.2500 100.0 489.05 605.13 1504.85 1310.94 10.52 15.49 394.19 2318.93 8760.33 1.26 45.41 371.28 2388.16 8117.91 8.6276 0.03 368 2319 100.00 28.50 17.0825
1 32 10.0038 0.2500 100.0 489.05 604.69 1509.93 1317.20 10.52 15.50 394.21 2318.93 8763.76 1.26 45.32 372.00 2388.10 8118.93 8.6558 0.03 369 2319 100.00 28.65 17.2355
1 33 0.0028 0.0000 100.0 518.67 643.13 1583.81 1404.98 14.62 21.61 553.55 2388.11 9039.84 1.30 47.61 521.55 2388.13 8126.15 8.4411 0.03 393 2388 100.00 39.01 23.2935
1 34 0.0012 0.0008 100.0 518.67 642.24 1587.04 1406.72 14.62 21.61 553.60 2388.15 9036.68 1.30 47.57 521.15 2388.13 8116.33 8.4196 0.03 392 2388 100.00 39.02 23.2997
1 35 10.0066 0.2510 100.0 489.05 605.25 1504.23 1306.63 10.52 15.49 394.24 2319.01 8765.65 1.26 45.48 371.35 2388.15 8114.43 8.6566 0.03 368 2319 100.00 28.74 17.1825
1 36 25.0050 0.6200 60.0 462.54 536.95 1271.16 1051.62 7.05 9.03 175.67 1915.18 7998.94 0.94 36.91 164.61 2027.94 7867.76 10.8817 0.02 307 1915 84.93 14.25 8.6697
1 37 10.0076 0.2500 100.0 489.05 604.84 1500.86 1311.00 10.52 15.49 394.31 2318.93 8764.83 1.26 45.41 371.34 2388.15 8109.56 8.6536 0.03 369 2319 100.00 28.40 17.1937
1 38 24.9987 0.6200 60.0 462.54 536.76 1261.64 1045.94 7.05 9.02 176.01 1915.16 8003.33 0.94 36.82 164.32 2027.95 7862.53 10.9054 0.02 306 1915 84.93 14.23 8.5581
1 39 24.9981 0.6211 60.0 462.54 536.66 1267.66 1057.66 7.05 9.02 176.03 1915.13 7994.34 0.94 36.57 164.19 2027.95 7865.11 10.9318 0.02 307 1915 84.93 14.44 8.6205
1 40 10.0065 0.2500 100.0 489.05 605.17 1505.09 1312.97 10.52 15.49 394.37 2318.94 8770.13 1.26 45.57 371.16 2388.16 8111.91 8.6373 0.03 370 2319 100.00 28.55 17.0936
1 41 25.0051 0.6211 60.0 462.54 536.74 1261.81 1048.78 7.05 9.02 175.76 1915.12 7997.12 0.94 36.95 164.97 2028.03 7862.39 10.8998 0.02 307 1915 84.93 14.37 8.5433
1 42 35.0029 0.8400 100.0 449.44 555.34 1365.14 1136.45 5.48 8.00 194.88 2222.69 8335.88 1.02 41.90 182.74 2387.72 8057.20 9.3769 0.02 334 2223 100.00 14.66 8.8740
1 43 42.0037 0.8409 100.0 445.00 549.78 1350.28 1127.59 3.91 5.71 138.88 2211.61 8309.94 1.02 41.95 131.44 2387.65 8070.12 9.3745 0.02 331 2212 100.00 10.58 6.3839
1 44 0.0002 0.0000 100.0 518.67 642.57 1582.90 1405.22 14.62 21.61 552.97 2388.16 9037.76 1.30 47.65 521.63 2388.16 8128.64 8.4635 0.03 393 2388 100.00 38.81 23.2704
1 45 35.0033 0.8400 100.0 449.44 555.28 1370.22 1129.04 5.48 8.00 194.41 2222.66 8338.36 1.02 41.91 182.67 2387.74 8051.91 9.3577 0.02 334 2223 100.00 14.82 9.0246
1 46 42.0046 0.8400 100.0 445.00 549.44 1354.85 1125.95 3.91 5.71 138.16 2211.61 8309.66 1.02 42.15 130.90 2387.63 8071.22 9.3717 0.02 331 2212 100.00 10.63 6.3498
1 47 10.0049 0.2500 100.0 489.05 605.01 1500.08 1309.65 10.52 15.50 394.09 2318.95 8763.10 1.26 45.52 371.27 2388.23 8115.46 8.6394 0.03 371 2319 100.00 28.57 17.1489
1 48 0.0004 0.0014 100.0 518.67 643.26 1588.58 1402.51 14.62 21.61 552.61 2388.16 9037.94 1.30 47.54 521.50 2388.12 8123.03 8.4318 0.03 392 2388 100.00 38.89 23.3464
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基于LSTM算法的航空发动机寿命预测
共440个文件
py:310个
dll:53个
pyd:25个
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2021-03-10
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对于航空发动机寿命预测问题,它的难点在于特征数数多,而且特征也是传感器所收集到的数据,传感器一般带有噪声,会造成拟合过程中的不准确性,设计一个多变量输入,单变量输出的预测模型,而RNN(循环神经网络)是一类以序列数据为输入,在序列演进方向进行递归且所有节点循环单元都按照链式连接的递归神经网络,它非常适合用作发动机寿命的预测模型,一方面,发动机数据具有时间信息,另一方面,单纯的RNN在处理数据时存在梯度消失问题。所以我们在RNN中引入LSTM(长短期记忆单元),这样可以很好解决上述两个问题
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基于LSTM算法的航空发动机寿命预测 (440个子文件)
activate 2KB
activate.bat 1KB
deactivate.bat 368B
sysconfig.cfg 3KB
pyvenv.cfg 89B
train.csv 9.11MB
test.csv 5.75MB
predict_test_fina4.csv 764KB
predict_test_fina5.csv 763KB
train_predict4.csv 9KB
train_predict5.csv 9KB
nvvm64_33_0.dll 9.54MB
python36.dll 3.45MB
tk86t.dll 1.87MB
tcl86t.dll 1.62MB
ucrtbase.dll 993KB
msvcp140.dll 611KB
vccorlib140.dll 378KB
concrt140.dll 322KB
msvcp140_2.dll 191KB
vcomp140.dll 152KB
vcruntime140.dll 85KB
api-ms-win-crt-private-l1-1-0.dll 70KB
python3.dll 50KB
msvcp140_1.dll 31KB
api-ms-win-crt-math-l1-1-0.dll 27KB
api-ms-win-crt-multibyte-l1-1-0.dll 26KB
api-ms-win-crt-string-l1-1-0.dll 24KB
api-ms-win-crt-stdio-l1-1-0.dll 24KB
api-ms-win-crt-runtime-l1-1-0.dll 23KB
api-ms-win-crt-convert-l1-1-0.dll 22KB
api-ms-win-core-file-l1-1-0.dll 22KB
api-ms-win-crt-time-l1-1-0.dll 21KB
api-ms-win-core-localization-l1-2-0.dll 21KB
api-ms-win-core-synch-l1-1-0.dll 20KB
api-ms-win-core-processthreads-l1-1-0.dll 20KB
api-ms-win-crt-filesystem-l1-1-0.dll 20KB
api-ms-win-crt-process-l1-1-0.dll 19KB
api-ms-win-core-libraryloader-l1-1-0.dll 19KB
api-ms-win-core-processenvironment-l1-1-0.dll 19KB
api-ms-win-crt-conio-l1-1-0.dll 19KB
api-ms-win-crt-heap-l1-1-0.dll 19KB
api-ms-win-core-sysinfo-l1-1-0.dll 19KB
api-ms-win-core-console-l1-1-0.dll 19KB
api-ms-win-core-heap-l1-1-0.dll 19KB
api-ms-win-core-timezone-l1-1-0.dll 19KB
api-ms-win-crt-environment-l1-1-0.dll 19KB
api-ms-win-crt-utility-l1-1-0.dll 19KB
api-ms-win-core-memory-l1-1-0.dll 19KB
api-ms-win-crt-locale-l1-1-0.dll 19KB
api-ms-win-core-rtlsupport-l1-1-0.dll 19KB
api-ms-win-core-processthreads-l1-1-1.dll 19KB
api-ms-win-core-synch-l1-2-0.dll 19KB
api-ms-win-core-string-l1-1-0.dll 18KB
api-ms-win-core-interlocked-l1-1-0.dll 18KB
api-ms-win-core-util-l1-1-0.dll 18KB
api-ms-win-core-file-l2-1-0.dll 18KB
api-ms-win-core-debug-l1-1-0.dll 18KB
api-ms-win-core-datetime-l1-1-0.dll 18KB
api-ms-win-core-errorhandling-l1-1-0.dll 18KB
api-ms-win-core-namedpipe-l1-1-0.dll 18KB
api-ms-win-core-file-l1-2-0.dll 18KB
api-ms-win-core-handle-l1-1-0.dll 18KB
api-ms-win-core-profile-l1-1-0.dll 18KB
setuptools-40.8.0-py3.6.egg 559KB
t64.exe 100KB
w64.exe 97KB
python.exe 91KB
t32.exe 91KB
pythonw.exe 90KB
w32.exe 87KB
easy_install-3.6.exe 73KB
pip3.6.exe 73KB
pip3.exe 73KB
pip.exe 73KB
easy_install.exe 73KB
RNN_test.iml 524B
not-zip-safe 1B
cacert.pem 269KB
PKG-INFO 3KB
predict_test_RUL5.png 386KB
predict_test_RUL4.png 379KB
predict_RUL4.png 263KB
predict_RUL5.png 251KB
Figure_4.png 18KB
Figure_5.png 17KB
训练过程4.PNG 14KB
训练误差4.PNG 14KB
训练过程及误差5.PNG 13KB
Activate.ps1 1KB
easy-install.pth 55B
setuptools.pth 31B
pyparsing.py 238KB
uts46data.py 194KB
html5parser.py 116KB
__init__.py 102KB
tarfile.py 90KB
constants.py 82KB
ipaddress.py 78KB
_tokenizer.py 75KB
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