Results 21 to 30 of about 3,652,100 (50)
On best approximation in fuzzy metric spaces [PDF]
, 2015 summary:In this paper we introduce the notation of t-best approximatively compact sets, t-best approximation points, t-proximinal sets, t-boundedly compact sets and t-best proximity pair in fuzzy metric spaces.
Abbasi, Naser, Mottaghi Golshan, Hamid
core +1 more source
Improvement of flight simulator feeling using adaptive fuzzy backlash compensation [PDF]
, 2007 In this paper we addressed the problem of improving the control of DC motors used for the specific application of a 3 degrees of freedom moving base flight simulator.
Bordeneuve-Guibé, Joël, Amara, Zied
core
Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter [PDF]
, 2011 When we try to analyze and to control a system whose model was obtained only based on input/output data, accuracy is essential in the model. On the other hand, to make the procedure practical, the modeling stage must be computationally efficient. In this
Jose Manuel Andujar Marquez +11 more
core +1 more source
Evolving Fuzzy Rule-based Classifiers from Data Streams [PDF]
, 2008 A new approach to the online classification of streaming data is introduced in this paper. It is based on a self-developing (evolving) fuzzy-rule-based (FRB) classifier system of Takagi-Sugeno ( eTS) type.
Angelov, Plamen, Zhou, Xiaowei
core +4 more sources
Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference [PDF]
, 2009 This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection ...
Yang, Bo-Suk +5 more
core +1 more source
On-line evolution of Takagi-Sugeno fuzzy models [PDF]
, 2004 Evolving Takagi-Sugeno (eTS) fuzzy models and the method for their on-line identification has been recently introduced for both MISO and MIMO case. In this paper, the mechanism for rule-base evolution, one of the central points of the algorithm together ...
Angelov, Plamen +7 more
core +2 more sources
BEHAVIOR BASED CONTROL AND FUZZY Q-LEARNING FOR AUTONOMOUS FIVE LEGS ROBOT NAVIGATION [PDF]
, 2009 This paper presents collaboration of behavior based control and fuzzy Q-learning for five legs robot navigation systems. There are many fuzzy Q-learning algorithms that have been proposed to yield individual behavior like obstacle avoidance, find target ...
Adil, Ratna
core
Designing a successful trading agent using fuzzy techniques
, 2004 Software agents are increasingly being used to represent humans in on-line auctions. Such agents have the advantages of being able to systematically monitor a wide variety of auctions and then make rapid decisions about what bids to place in what ...
He, M. +3 more
core
EMBEDDED LEARNING ROBOT WITH FUZZY Q-LEARNING FOR OBSTACLE AVOIDANCE BEHAVIOR [PDF]
, 2009 Fuzzy Q-learning is extending of Q-learning algorithm that uses fuzzy inference system to enable Q-learning holding continuous action and state. This learning has been implemented in various robot learning application like obstacle avoidance and target ...
Anam, Khairul
core