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teaching scenarios both supported on an existing Hardware-in-the-Loop (HIL) equipment, enabling students to deploy their own control algorithms, state eObjectives By the end of the three-month period, the
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, allowing adapting to several conditions of use and to be managed automatically. AI algorithms will be selected, trained and tested. WP7 – Communication, dissemination and exploitation: Support for
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, Automation, Machine Learning and Artificial Intelligence, Sensor Networks, Hierarchical Decision and Control Systems, with a primary focus on manufacturing and autonomous systems. (1 to 5 points); C
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Artificial Intelligence, Sensor Networks, Hierarchical Decision and Control Systems, with a primary focus on manufacturing and autonomous systems. (1 to 5 points); C. Knowledge and Experience of participating
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real-time optimization algorithm for a simulated moving bed system to correct possible mismatches between the mathematical model and the real process. The approach to be developed is based on modifier
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available in the further tabs (e.g. “Application requirements”). Programme Description The research and training programme focusses on the mathematical and algorithmic foundations of reliable AI along with
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mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering, or neural networks). Non-negative tensor factorization