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1 Ergebnisse
1
A Novel Model Based on PSO-GA-RBF Approach for Predicting R..:
, In:
2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)
,
Zhang, Ruixiao
;
Mao, Chaoxing
;
Hu, Jinkai
.. - p. 636-641 , 2024
Link:
https://doi.org/10.1109/EEBDA60612.2024.10485850
RT T1 <cTitle>2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)</cTitle>: T1 <Title>A Novel Model Based on PSO-GA-RBF Approach for Predicting Roll Gap During Unsteady Processes</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10485850&Exemplar=1&LAN=DE A1 Zhang, Ruixiao A1 Mao, Chaoxing A1 Hu, Jinkai A1 Liu, Zhao A1 Guo, Hengda YR 2024 K1 Training K1 Strips K1 Process control K1 Production K1 Predictive models K1 Big Data K1 Data models K1 Thickness control K1 Roll gap model K1 Radial basis function neural network K1 Particle swarm optimization algorithm K1 Genetic algorithm SP 636 OP 641 LK http://dx.doi.org/https://doi.org/10.1109/EEBDA60612.2024.10485850 DO https://doi.org/10.1109/EEBDA60612.2024.10485850 SF ELIB - SuUB Bremen
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