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Machine Learning Algorithm-Based Discovery of Potential Regulators of Immune-Related Dilated Cardiomyopathy. [PDF]
Acta Cardiol SinYang YT +5 more
europepmc +1 more source
Learning-based orchestration for low-latency AI deployment in hybrid cloud-edge platforms. [PDF]
Sci RepAlbugmi A.
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Scheduling with batching: A review
European Journal of Operational Research, 2000 There is an extensive literature on models that integrate scheduling with batching decisions. Jobs may be batched if they share the same setup on a machine. Another reason for batching occurs when a machine can process several jobs simultaneously.
Mikhail Yakovlevich Kovalyov +1 more
exaly +2 more sources
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Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2004
When designing steady-state computer simulation experiments, one may be faced with the choice of batching observations in one long run or replicating a number of smaller runs. Both methods are potentially useful in the course of undertaking simulation output analysis.
Christos Alexopoulos, David Goldsman
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When designing steady-state computer simulation experiments, one may be faced with the choice of batching observations in one long run or replicating a number of smaller runs. Both methods are potentially useful in the course of undertaking simulation output analysis.
Christos Alexopoulos, David Goldsman
openaire +1 more source
Batch-to-batch Optimization of Batch Crystallization Processes
Chinese Journal of Chemical Engineering, 2008Abstract It is the fact that several process parameters are either unknown or uncertain. Therefore, an optimal control profile calculated with developed process models with respect to such process parameters may not give an optimal performance when implemented to real processes.
Woranee Paengjuntuek +2 more
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Batch-to-batch strategies for cooling crystallization
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012Two batch-to-batch (B2B) algorithms for supersaturation control in cooling crystallization are presented in this paper. In Iterative Learning Control (ILC) a nominal process model is adjusted with an additive correction term which depends on the error in the last batch.
Marco Forgione +3 more
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Proceedings of the 2005, American Control Conference, 2005., 2005
An integrated batch-to-batch iterative learning control (ILC) and within batch on-line shrinking horizon model predictive control (SHMPC) strategy for the tracking control of product qualities in batch processes is proposed. ILC is used for batch-to-batch control based on a batch-wise linear time-varying (LTV) perturbation model and the convergence of ...
Zhihua Xiong +3 more
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An integrated batch-to-batch iterative learning control (ILC) and within batch on-line shrinking horizon model predictive control (SHMPC) strategy for the tracking control of product qualities in batch processes is proposed. ILC is used for batch-to-batch control based on a batch-wise linear time-varying (LTV) perturbation model and the convergence of ...
Zhihua Xiong +3 more
openaire +2 more sources