Titlebook: Computational Intelligence and Optimization Methods for Control Engineering; Maude Josée Blondin,Panos M. Pardalos,Javier Sanch Book 2019

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https://doi.org/10.1007/3-540-29983-1added to the routes to simulate “real” road and daily operation conditions. This data is used for monitoring the energetic key performance factors by learning from the buses with the best energetic behavior. Finally, a decision-making process is applied to improve the local energy management of the

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Computational Intelligence in the Desalination Industry,y sources to directly power these plants. This has added new challenges to the management of desalination processes as the temporal variability of renewable energy sources makes the decision-making processes more complicated. In turn, this means that a multivariable approach is required to ensure op

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A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems,physical interactions of neighboring agents as well as physical-human interactions, and finally to dynamically model and optimize the overall networked system. The hierarchical structure makes the overall optimization and control problem scalable and solvable. Moreover, the three levels integrate in

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Coherency Estimation in Power Systems: A Koopman Operator Approach,ording to the penetration level or fault location. The applied method of coherency identification is evaluated in the Nordic test system through gradually increasing integration of non-synchronous generations and different fault scenarios.

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