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Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and...
We consider the problem of optimal control for a kind of uncertain networked systems which are composed of some heteromorphic subsystems in this paper. For the trouble of encountering the complex structure, the unavoidable uncertainties and/or disturbances of networked systems, we try to remove or eliminate the interconnected parts, uncertainties and disturbances from the system by using the method...
The performances of supervised learning techniques on image classification problems heavily rely on the quality of their training images. But the acquisition of high quality training images requires significant efforts from human annotators. In this paper, we propose a novel multi-label batch model active learning (MLBAL) approach that allows the learning algorithm to actively select a batch of informative...
On-line optimization and control of fed-batch fermentation is difficult due to its non linearity and dynamic operation points with uncertainty. A novel cascade optimal control algorithm was proposed to treat these difficulties with the operating points, which maximize the objective function, was defined by Necessary Conditions of Optimization (NCO). Consequently, a nonlinear Generic Model Control...
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