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» An approach to stopping problems of a dynamic fuzzy system
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ICTAI
2005
IEEE
15 years 7 months ago
Hybrid Learning Neuro-Fuzzy Approach for Complex Modeling Using Asymmetric Fuzzy Sets
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...
Chunshien Li, Kuo-Hsiang Cheng, Jiann-Der Lee
FSS
2008
134views more  FSS 2008»
15 years 1 months ago
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets
In the field of classification problems, we often encounter classes with a very different percentage of patterns between them, classes with a high pattern percentage and classes w...
Alberto Fernández, Salvador García, ...
IJON
2006
134views more  IJON 2006»
15 years 1 months ago
A new approach to fuzzy classifier systems and its application in self-generating neuro-fuzzy systems
A classifier system is a machine learning system that learns syntactically simple string rules (called classifiers) through a genetic algorithm to guide its performance in an arbi...
Mu-Chun Su, Chien-Hsing Chou, Eugene Lai, Jonathan...
SIAMSC
2010
132views more  SIAMSC 2010»
14 years 11 months ago
A Posteriori Error Estimates Including Algebraic Error and Stopping Criteria for Iterative Solvers
For the finite volume discretization of a second-order elliptic model problem, we derive a posteriori error estimates which take into account an inexact solution of the associated...
Pavel Jiránek, Zdenek Strakos, Martin Vohra...
CDC
2010
IEEE
139views Control Systems» more  CDC 2010»
14 years 8 months ago
Q-learning and enhanced policy iteration in discounted dynamic programming
We consider the classical finite-state discounted Markovian decision problem, and we introduce a new policy iteration-like algorithm for finding the optimal state costs or Q-facto...
Dimitri P. Bertsekas, Huizhen Yu