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» The importance of learning in fuzzy systems
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ARTCOM
2009
IEEE
14 years 2 months ago
ANFIS Approach for Navigation of Mobile Robots
— This paper, discusses about navigation control of mobile robot using adaptive neuro-fuzzy inference system (ANFIS) in a real word dynamic environment. In the ANFIS controller a...
Mukesh Kumar Singh, Dayal R. Parhi, Jayanta Kumar ...
EUSFLAT
2003
115views Fuzzy Logic» more  EUSFLAT 2003»
13 years 9 months ago
A hierarchical fuzzy rule-based learning system based on an information theoretic
This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human...
Antony Waldock, Brian Carse, Chris Melhuish
SMC
2007
IEEE
132views Control Systems» more  SMC 2007»
14 years 1 months ago
Disaster management model based on Modified Fuzzy Cognitive Maps
-This paper describes the use of a Fuzzy Cognitive Map (FCM) to model disaster reconstruction, based on data collected from the cities of BAM and Baravat. The extended fuzzy cognit...
Sandeep Chandana, Henry Leung, Jason Levy
ICANN
2001
Springer
14 years 21 hour ago
The Importance of Representing Cognitive Processes in Multi-agent Models
We distinguish between two main types of model: predictive and explanatory. It is argued (in the absence of models that predict on unseen data) that in order for a model to increas...
Bruce Edmonds, Scott Moss
ESANN
2003
13 years 9 months ago
A Fuzzy ARTMAP Probability Estimator with Relevance Factor
Abstract. An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzz...
Razvan Andonie, Lucian Sasu