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» Learning maximal structure fuzzy rules with exceptions
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TFS
2008
157views more  TFS 2008»
13 years 5 months ago
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
Cheng-Jian Lin, Cheng-Hung Chen, Chin-Teng Lin
EGICE
2006
13 years 9 months ago
Evolutionary Generation of Implicative Fuzzy Rules for Design Knowledge Representation
Abstract. In knowledge representation by fuzzy rule based systems two reasoning mechanisms can be distinguished: conjunction-based and implication-based inference. Both approaches ...
Mark Freischlad, Martina Schnellenbach-Held, Torbe...
ROBOCUP
2001
Springer
111views Robotics» more  ROBOCUP 2001»
13 years 10 months ago
Evolving Fuzzy Logic Controllers for Sony Legged Robots
This paper presents an evolutionary approach to learning a fuzzy logic controller(FLC) employed for reactive behaviour control of Sony legged robots. The learning scheme is divided...
Dongbing Gu, Huosheng Hu
OGAI
1993
13 years 10 months ago
Combining Neural Networks and Fuzzy Controllers
Fuzzy controllers are designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory ...
Detlef Nauck, Frank Klawonn, Rudolf Kruse
AIIA
2001
Springer
13 years 10 months ago
A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data
– This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning al...
Giovanna Castellano, Anna Maria Fanelli