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Titlebook: Advances and Trends in Artificial Intelligence. From Theory to Practice; 32nd International C Franz Wotawa,Gerhard Friedrich,Moonis Ali Con

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H. Margreet Oerlemans,Rob A. B. Oostendorpcal Outlier Factor (LOF) algorithm to extend a closed-set classifier (i.e. multilayer perceptron) with an additional class that identifies outliers. The analyzed text documents are represented by averaged word embeddings calculated using the fastText method on training data. Conducting the experimen
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Zenuwblokkades voor behandeling van CRPS I,pose is based on the implicit stochastic optimization (ISO) framework, using direct policy search methods combined with deep neural networks (DNN). The findings from a real-world two-reservoir hydropower system in southern Norway suggest that DNNs can learn how to map input (price, inflow, starting
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Boekblok Praktijkboek tandheelkundereact appropriately in case of a fault occurring during driving on a highway in order to assure safety for passengers and other humans in its surrounding. Hence, there is a need for fail-operational systems that extend the concept of fail-safety. In this paper, we introduce a method that relies on r
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H. van den Berg,C.F.J. van Tuijnhe current methods to monitor these parameters, this work proposes the use of a UAV for commercial use and the construction of a card for gas measurement. Additionally and with the objective of having complete control over the vehicle, the article proposes the development of a library for the contro
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P.H. van de Voort,G.P.M. Bakkerthe business domain, capturing user requirements, and developing adequate IT solutions taking into consideration these changes and answering user needs. CORE aims at providing continuously a certain level of quality (business, service, security, etc.) in dynamically changing circumstances such as sm
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Advances and Trends in Artificial Intelligence. From Theory to Practice978-3-030-22999-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Inleiding en voorgeschiedenis WKCZ,ly a cross-disciplinary problem. This paper introduces a generic taxonomy of event prediction approaches. The proposed taxonomy, which oversteps the application domain, enables a better understanding of event prediction problems and allows conceiving and developing advanced and context-independent event prediction techniques.
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