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
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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
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Methods of analysing ordinal/interval questionnaire data using fuzzy mathematical principle [PDF]
, 2007 Two methods of analysing interval/ordinal questionnaire data based upon principles from fuzzy mathematics and artificial intelligence are ...
Hassall, John
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Matrix formulation of fuzzy rule-based systems [PDF]
, 1996 In this paper, a matrix formulation of fuzzy rule based systems is introduced. A gradient descent training algorithm for the determination of the unknown parameters can also be expressed in a matrix form for various adaptive fuzzy networks.
Lotfi, A, Andersen, HC, Tsoi, AC
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Zero overshoot and fast transient response using a fuzzy logic controller [PDF]
, 2012 In some industrial process control systems it is desirable not to allow an overshoot beyond the setpoint or a threshold, this could be a safety constraint or the requirement of the system.
Mehrdadi, Bruce, Saeed, Bakhtiar I.
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Hidden fuzzy information: Requirement specification and measurement of project provider performance using the best worst method [PDF]
, 2020 The requirement specification process is an important part of a project and has the potential to prevent problems that may last for years after a project is delivered.
Asadabadi, Mehdi Rajabi +4 more
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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
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Fuzzy and tile coding approximation techniques for coevolution in reinforcement learning [PDF]
, 2005 PhDThis thesis investigates reinforcement learning algorithms suitable for learning in large state space problems and coevolution. In order to learn in large state spaces, the state space must be collapsed to a computationally feasible size and then ...
Tokarchuk, Laurissa Nadia
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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
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VHDL-AMS based genetic optimisation of fuzzy logic controllers
, 2007 Purpose – This paper presents a VHDL-AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains.
Wang, Leran, Kazmierski, Tom
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