extended fuzzy logic
From fuzzy logic to extended fuzzy logic–a first step
FREE-DOWNLOAD LA Zadeh – Presentation made at the North American Fuzzy …, 2009
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Maximum power point tracking using fuzzy logic control for photovoltaic systems
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In this paper, a fuzzy logic control (FLC) is proposed to control the maximum power point tracking (MPPT) for a photovoltaic (PV) system. The proposed technique uses the fuzzy logic control to specify the size of incremental current in the current command of MPPT. As results
A fuzzy logic for autonomous navigation of marine vehicles satisfying COLREG guidelines
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An autonomous navigation algorithm for marine vehicles is proposed in this paper using fuzzy logic under COLREG guidelines. The VFF (Virtual Force Field) method, which is widely used in the field of mobile robotics, is modified for application to the autonomous navigation
Fuzzy logic -based risk assessment
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Safety and reliability are essential issues in modern sciences. Modern equipment and systems should meet technical, safety and environmental protection requirements. The risk can appear as personal injury or death, mission degradation, property technical damage or1 Introduction 60 2 Max-min operator networks and fuzzy 8 rule 62 3 Theoretical results 68 4 Fuzzy bidirectional associative memory 73 5 Max-times operator networks 75 6 An extended fuzzy neuron and network 77 7 Relationship with t-norm and t-conorm 80 8 A novel training
Integrating fuzzy logic with data mining methods for intrusion detection
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This report explores integrating fuzzy logic with two data mining methods (association rules and frequency episodes) for intrusion detection. Data mining methods are capable of extracting patterns automatically from a large amount of data. The integration with fuzzy logic
Measuring uncertainty in class assignment for natural resource maps under fuzzy logic
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There are two kinds of uncertainty associated with assigning a geographic entity to a class in the classification process. The first is related to the fuzzy belonging of the entity to the prescribed set of classes and the second is associated with the deviation of the entity from
Definiton of neutrosophic logic -a generalization of the intuitionistic fuzzy logic .
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In this paper one generalizes the intuitionistic fuzzy logic (IFL) and other logics to neutrosophic logic (NL). The differences between IFL and NL (and the corresponding intuitionistic fuzzy set and neutrosophic set) are pointed out Keywords and Phrases: Non-Standard Analysis, Paraconsistent
Fuzzy logic controllers. Advantages and drawbacks
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In this papei, an. analysis of the iole of fuzzy logic controllers is carried out. Its interpretation and the conditions for successful implementation in several control structures, jointly with their advantages and drawbacks with relation to other advanced control approaches are
A fuzzy logic based robot navigation system
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One of the key issues in mobile robot navigation is coping with uncertainty in a dynamic environment. One possible solutions lies in behaviors, but there is a problem with standard behavior arbitration techniques. To combat this problem, David Payton introduced a
Efficient load balancing in cloud computing using fuzzy logic
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Cloud computing is an expanding area in research and industry today, which involves virtualization, distributed computing, internet, software and web services. A cloud consists of several elements such as clients, data centers and distributed servers, internet and it
Delayed reinforcement, fuzzy Q-learning and fuzzy logic controllers
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In this paper, we discuss situations arising with reinforcement learning algorithms, when the reinforcement is delayed. The decision to consider delayed reinforcement is typical in many applications, and we discuss some motivations for it. Then, we summarize Q-Learning, a
Intelligent Control of an Autonomous Mobile Robot using Type-2 Fuzzy Logic .
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We develop a tracking controller for the dynamic model of unicycle mobile robot by integrating a kinematic controller and a torque controller based on Fuzzy Logic Theory. Computer simulations are presented confirming the performance of the tracking controller
Fuzzy logic control of doubly fed induction generator wind turbine
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This paper presents fuzzy logic control of Doubly Fed Induction Generator (DFIG) wind turbine in a sample power system. DFIG consists of a common induction generator with slip ring and a partial scale power electronic converter. Fuzzy logic controller is applied to rotor
Paradigm shift-an introduction to fuzzy logic
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JANUARY/FEBRUARY 2006 7 and the current system state. Using fuzzy arithmetic, one uses a model and makes a subset of the system components fuzzy so that fuzzy arithmetic must be used when executing the model. In a broad sense, fuzzy logic refers to fuzzy sets
A fuzzy logic system for process monitoring and quality evaluation in GMAW
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This paper introduces a fuzzy logic system that is able to recognize common disturbances during automatic gas metal arc welding (GMAW) using measured welding voltage and current signals. A statistical method was employed to process the captured transient raw
Fuzzy logic based image edge detection algorithm in MATLAB
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This paper reports the implementation, in MATLAB environment, of a very simple but efficient fuzzy logic based algorithm to detect the edges of an input image by scanning it throughout using a 2* 2 pixel window. Also, a Graphical User Interface (GUI) in MATLAB has been
Comparison between prediction capabilities of neural network and fuzzy logic techniques for L and slide susceptibility mapping
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Preparation of L and slide susceptibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of L and slides, producing a reliable susceptibility map is not easy. In recent years, various data mining and soft computing
Intrusion detection using data mining along fuzzy logic and genetic algorithms
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Intrusion Detection is one of the important area of research. Our work has explored the possibility of integrating the fuzzy logic with Data Mining methods using Genetic Algorithms for intrusion detection. The reasons for introducing fuzzy logic is two fold, the first being the
Integrating fuzzy logic in ontologies.
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Ontologies have proved to be very useful in sharing concepts across applications in an unambiguous way. Nowadays, in ontology-based applications information is often vague and imprecise. This is a well-known problem especially for semantics-based applications
A fuzzy logic based reputation model against unfair ratings
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Reputation systems have become more and more important in facilitating transactions in online systems. However, the accuracy of reputation systems has always been a concern for the users due to the existence of unfair ratings. Though many approaches have been