Titlebook: Information Processing and Management of Uncertainty in Knowledge-Based Systems; 19th International C Davide Ciucci,Inés Couso,Ronald R. Ya

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Nonlinear Weighted Independent Component Analysisa new nonlinear ICA model, called WICA, which obtains better and more stable results than other algorithms. A crucial tool is given by a new efficient method of verifying nonlinear dependence with the use of computation of correlation coefficients for normally weighted data. In addition, we propose

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Statistical Models for Partial Orders Based on Data Depth and Formal Concept Analysisbservation of data. After discussing some shortcomings of distance based models in this context, we introduce statistical models for partial orders based on the notion of data depth. Here we use the rich vocabulary of formal concept analysis to utilize the notion of data depth for the case of partia

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Prescriptive Analytics for Optimization of FMCG Delivery Plans happen. In this paper, we propose a prescriptive framework for optimizing sales and profits of companies operating in the fast-moving consumer goods (FMCG) market. We discuss the key aspects of the framework and demonstrate its effectiveness in a series of experiments on real-world data. We compare

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Reciprocal Preference-Aversion Structuresy the bipolar approach of that model with the simplicity resulting from imposing additive reciprocity constraints on the basic, positive/negative standard fuzzy preference structures from which the P-A model is built. Thus, the proposed reciprocal P-A model is instead built from a pair of compatible

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Calibration of Radiation-Induced Cancer Risk Models According to Random Dataor metrology system, measurement noise, missing or uncontrollable input variables, or by the inability to directly measure the inputs and/or outputs of interest. The forward approach performs the calibration in the space of the model’s output thereby requiring repeated model simulations. Conversely,

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