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Information Processing and Management of Uncertainty in Knowledge-Based Systems: 20th International Conference, IPMU 2024, Lisbon, Portugal, July 22-26, 2024, Proceedings, Volume 3 2025 ed. [Mīkstie vāki]

  • Formāts: Paperback / softback, 390 pages, height x width: 235x155 mm, 88 Illustrations, color; 28 Illustrations, black and white; XXII, 390 p. 116 illus., 88 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Networks and Systems 1176
  • Izdošanas datums: 13-Feb-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031739965
  • ISBN-13: 9783031739965
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 180,78 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 212,69 €
  • Ietaupiet 15%
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  • Daudzums:
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  • Piegādes laiks - 4-6 nedēļas
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  • Formāts: Paperback / softback, 390 pages, height x width: 235x155 mm, 88 Illustrations, color; 28 Illustrations, black and white; XXII, 390 p. 116 illus., 88 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Networks and Systems 1176
  • Izdošanas datums: 13-Feb-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031739965
  • ISBN-13: 9783031739965
Citas grāmatas par šo tēmu:
This book is a collection of papers focused on techniques for managing uncertainty and aggregation. It provides a forum for exchanging ideas between theoreticians and practitioners in these and related areas.





The papers are part of the 20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, which will occur in Lisbon, Portugal, from July 22 to 26, 2024.





The collection describes the latest findings on topics such as advances in fuzzy systems and data analysis, optimization, scheduling via modeling uncertainty, explainability, decision-making, implications, data aggregation, and aggregation operators. A special chapter is dedicated to the memory of Michio Sugeno.





The book is a valuable resource for practitioners, researchers, and graduate students who want to apply fuzzy-based techniques to real-world data analysis and management processes involving imprecision and uncertainty.

Suppressing impulse noise via cloud filtering.- A Proposed Liver Cancer Classification.- Estimating the registration error of brain MRI data based on regression U-Net.- User-friendly health-conscious recipe adaptation system using fuzzy linguistic variables.- Unveiling Hidden Patterns in Clinical Databases: A Novel Approach Using Level-By-Level Association Rule Mining.