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FOCI 2011 : 2011 IEEE Symposium on Foundations of Computational Intelligence

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Conference Series : Foundations of Computational Intelligence
 
Link: http://www.ieee-ssci.org/2011/foci-2011
 
When Apr 11, 2011 - Apr 15, 2011
Where Paris, France
Submission Deadline Oct 31, 2010
Notification Due Dec 15, 2010
Final Version Due Jan 15, 2011
Categories    computational intelligence   artificial intelligence
 

Call For Papers

Part of IEEE Symposium Series on Computational Intelligence 2011

Computational intelligence techniques have proven useful after numerous applications in real world problems. However, there is much work to be done in order to fully understand the theoretical foundations of such techniques. IEEE FOCI'11, provides an ideal forum for those who are interested in the fundamental issues of computational intelligence to exchange their ideas and present their latest findings.
IEEE FOCI'11 will focus on fundamental theoretical and practical foundations of computational intelligence, including but not limited to neural networks, fuzzy logic, evolutionary computation, and other machine learning methods. The symposium will put equal emphasis on theoretical and practical work as long as it addresses the foundations of computational intelligence.


Topics

* Non-standard fuzzy sets (e.g., type-2, interval-valued, random-fuzzy, fuzzy-random, etc.)
* Granular computing
* Computing with words
* Aggregation/fusion
* Fuzzy sets and statistics
* Uncertainty
* Decision-making
* General theoretical issues
* Generalisation in neural, fuzzy and evolutionary learning
* Fuzzy logic and fuzzy set theory
* Lattice theory and multi-valued logic
* Approximate reasoning
* Type-2 fuzzy logic
* Rough sets and random sets
* Fuzzy mathematics
* Fuzzy measure and integral
* Possibility theory and imprecise probability

* Neural computation
* Self-organizing maps
* Recurrent networks
* Multilayer perceptrons
* Recursive deterministic perceptrons
* Evolutionary neural networks
* Neural networks for pattern recognition
* Neural networks for principal component analysis
* General regression neural networks
* Neural networks as/and fuzzy systems
* Radial basis functions
* Learning theory
* Generalization in neural networks


Symposium Co-Chairs

Manuel Ojeda-Aciego, University of Malaga, Spain
Carlos Cotta, University of Malaga, Spain
Francisco Veredas, University of Malaga, Spain

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