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Titlebook: Handbuch des Investmentsparens; Rüdiger H. Päsler Book 1991 Betriebswirtschaftlicher Verlag Dr. Th. Gabler GmbH, Wiesbaden 1991 Aktien.Akt

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namely: i) Autonomous Systems; ii) Pattern Recognition and Vision Systems; iii) E-Enabled Systems; iv) Mobile Computing and Intelligent Networking; v) Internet and Cloud Computing; vi) Intelligent Systems, and 978-3-319-69095-7978-3-319-69096-4Series ISSN 2194-5357 Series E-ISSN 2194-5365
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Rüdiger H. Päslerl models of the physical device. According to the specific needs of the operation and maintenance of the physical device, the component-level monitoring data (operating conditions, thyristors, water level, temperature and humidity, etc.) of the physical device are overlaid onto the corresponding equipment model.
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Rüdiger H. Päslerally calls for probabilistic approaches. In this chapter, I will describe techniques and issues involved in building probabilistic student models based on Bayesian networks and their extensions. I will describe pros and cons of this approach, and discuss examples from existing Intelligent Tutoring Systems that rely on Bayesian student models
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Rüdiger H. Päslernd compare with the modified calculated value of rolling force, which got from the self-learning model of rolling force. The results show that the thickness can be predicted more rapidly and exactly, which can meet the actual demand of production, when this model and the rolling force learning model are integrated.
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Rüdiger H. Päslerult change rule and reliability level of new energy vehicles, and provides basic support for improving the reliability of new energy vehicles, reducing maintenance costs, expanding consumers’ purchase choices, and improving the sales volume of new energy vehicles.
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