Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations : 17th International Conference, IPMU 2018, C¡diz, Spain, June 11-15, 2018, Proceedings, Part II - Jesús Medina

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

17th International Conference, IPMU 2018, C¡diz, Spain, June 11-15, 2018, Proceedings, Part II

By: Jesús Medina (Editor), Manuel Ojeda-Aciego (Editor), José Luis Verdegay (Editor)

Paperback | 18 May 2018

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This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cadiz, Spain, in June 2018.

The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).

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