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Fuzzy Logic in Artificial Intelligence: IJCAI'97 Workshop Nagoya, Japan, August 23-24, 1997 Selected and Invited Papers: Lecture Notes in Computer Science, cartea 1566

Editat de Anca L. Ralescu, James G. Shanahan
en Limba Engleză Paperback – 28 iul 1999
This volume constitutes the thoroughly refereed post-workshop proceedings of an international workshop on fuzzy logic in Artificial Intelligence held in Negoya, Japan during IJCAI '97.
The 17 revised full papers presented have gone through two rounds of reviewing and revision. Three papers by leading authorities in the area are devoted to the general relevance of fuzzy logic and fuzzy sets to AI. The remaining papers address various relevant issues ranging from theory to application in areas like knowledge representation, induction, logic programming, robotics, pattern recognition, etc.
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Specificații

ISBN-13: 9783540663744
ISBN-10: 3540663746
Pagini: 264
Ilustrații: CCLXIV, 254 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.37 kg
Ediția:1999
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Some reflections on the relationship between AI and fuzzy logic (FL) —A heretical view.- The place of fuzzy logic in AI.- Mass assignment fundamentals for computing with words.- A method to use uncertain domain knowledge in the induction of classification knowledge based on ID3.- Fril++ a language for object-oriented programming with uncertainty.- Case-based reasoning: A fuzzy approach.- System identification of fuzzy cartesian granule feature models using genetic programming.- Deep fusion of symbolic and computational processing for next generation user interface.- Reasoning with words about geographic information.- Fuzzy morphology and fuzzy distances: New definitions and links in both euclidean and geodesic cases.- An application of possibility theory information fusion to satellite image classification.- Pattern recognition of strong graphs based on possibilistic c-means and k-formulae matching.- A fuzzy-neural model for co-ordination in air traffic flow management.- From numerical interpolation to constructing intelligent behaviours.- A brief logopedics for the data used in a Neuro-fuzzy milieu.- Evaluation of fuzzy quantified expressions.

Caracteristici

Includes supplementary material: sn.pub/extras