Uncertainty Modeling Dedicated to Professor Boris Kovalerchuk on his Anniversary - Kreinovich, Vladik; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2017)
This book commemorates the 65th birthday of Dr. Boris Kovalerchuk, and reflects many of the research areas covered by his work. It focuses on data processing under uncertainty, especially fuzzy data processing, when uncertainty comes from the imprecision of expert opinions. The book includes 17 authoritative contributions by leading experts.
Preface -- MapReduce: From Elementary Circuits to Cloud -- On the Helmholtz Principle for Data Mining -- A method of introducing weights into OWA operators and other symmetric functions -- Uncertainty Management: Probability, Possibility, Entropy, and Other Paradigms- Relationships between fuzziness, partial truth and probability in the case of repetitive events -- Using extended tree kernels to recognize metalanguage in text -- Relationships between Probability and Possibility Theories -- Modeling extremal events is not easy: why the Extreme Value Theorem cannot be as general as the Central Limit Theorem -- Information quality and uncertainty -- Applying anomalous cluster approach to spatial clustering -- Why is linear quantile regression empirically successful: a possible explanation -- A Rapid Soft Computing Approach to Dimensionality Reduction in Model Construction -- Physics Of The Mind, Dynamic Logic, and Monotone Boolean Functions -- Fuzzy arithmetic type 1 without extension principle and vertical membership functions -- Copula as a bridge between probability theory and fuzzy logic -- Note to the polemics surrounding the second Goedel's theorem -- Ontological Data Mining.
Keywords: Computational intelligence; Artificial intelligence; Computational Intelligence; Artificial Intelligence