Blast furnace iron-making process (BFIP) is one of the most critical procedures in the iron and steel industry, in which timely detection and accurate classification of faults have always been of core focus. Nevertheless, due to the coupling effects of complex nonlinear and nonstationary characteristics hidden among the data, the consistent underlying information in the process cannot be accurately mined, hindering the establishment of the BFIP fault diagnosis model.

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[1] Siwei Lou, "Joint model based on RMK-ASSA and DBSKNet", IEEE Dataport, 2022. [Online]. Available: http://dx.doi.org/10.21227/r31v-vy73. Accessed: Sep. 15, 2024.
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doi = {10.21227/r31v-vy73},
url = {http://dx.doi.org/10.21227/r31v-vy73},
author = {Siwei Lou },
publisher = {IEEE Dataport},
title = {Joint model based on RMK-ASSA and DBSKNet},
year = {2022} }
TY - DATA
T1 - Joint model based on RMK-ASSA and DBSKNet
AU - Siwei Lou
PY - 2022
PB - IEEE Dataport
UR - 10.21227/r31v-vy73
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Siwei Lou. (2022). Joint model based on RMK-ASSA and DBSKNet. IEEE Dataport. http://dx.doi.org/10.21227/r31v-vy73
Siwei Lou, 2022. Joint model based on RMK-ASSA and DBSKNet. Available at: http://dx.doi.org/10.21227/r31v-vy73.
Siwei Lou. (2022). "Joint model based on RMK-ASSA and DBSKNet." Web.
1. Siwei Lou. Joint model based on RMK-ASSA and DBSKNet [Internet]. IEEE Dataport; 2022. Available from : http://dx.doi.org/10.21227/r31v-vy73
Siwei Lou. "Joint model based on RMK-ASSA and DBSKNet." doi: 10.21227/r31v-vy73