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Modeling Decisions for Artificial Intelligence de Vicenç Torra

Modeling Decisions for Artificial Intelligence: Lecture Notes in Computer Science, cartea 11144

Editat de Vicenç Torra, Yasuo Narukawa, Isabel Aguiló, Manuel González-Hidalgo
en Limba Engleză Paperback – 16 sep 2018
This book constitutes the proceedings of the 15th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2018, held in Mallorca, Spain, in October 2018. The 24 papers presented in this volume were carefully reviewed and selected from 43 submissions. The book also contains one invited talk in full paper length. The papers were organized in topical sections named: aggregation operators, fuzzy measures and integrals; decision making; clustering and classification; and data privacy and security.
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Specificații

ISBN-13: 9783030002015
ISBN-10: 3030002012
Pagini: 348
Ilustrații: XXV, 319 p. 149 illus., 24 illus. in color.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.53 kg
Ediția:1st ed. 2018
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Invited Paper.- Graded logic aggregation.- Aggregation Operators, Fuzzy Measures and Integrals.- Coherent Risk Measures Derived from Utility Functions.- On k-+-additive Aggregation Functions.- Constructing an outranking relation with weighted OWA for multi-criteria decision analysis.- Sugeno integrals and the commutation problem.- Event-based Transformations of Set Functions and The Consensus Requirement.- Association Analysis on Interval-valued Fuzzy Sets.- Fuzzy Hit-or-Miss Transform Using Uninorms.- Learning fuzzy measures for aggregation in fuzzy rule-based models.- Decision making.- Extraction of Patterns to support Dairy Culling Management.- An axiomatisation of the Banzhaf value and interaction index for multichoice games.- Fuzzy Positive Primitive Formulas.- Basic Level Concepts as a Means to Better Interpretability of Boolean Matrix Factors and their Application to Clustering.- Fuzzy type powerset operators and F-transforms.- Implicative weights as Importance Quantifiers in Evaluation Criteria.- Balancing Assembly Lines and Matching Demand through Worker Reallocations.- Clustering and Classification.- Optimal Clustering with Twofold Memberships.- Privacy Preserving Collaborative Fuzzy Co-clustering of Three-mode Cooccurrence Data.- Generalized Fuzzy c-Means Clustering and Its Theoretical Properties.- A self-tuning possibilistic c-means clustering algorithm.- k-CCM: A Center-Based Algorithm for Clustering Categorical Data with Missing Values.- Data privacy and security.- WEDL-NIDS:Improving Network Intrusion Detection using Word Embedding-based Deep Learning Method.- Anonymization of Unstructured Data Via Named-Entity Recognition.- On the Application of SDC Stream Methods to Card Payments Analytics.