Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"Fuzzy logic systems"”.
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Geometric Fuzzy Logic Systems
… in academic interest in the field oftype-2 fuzzy sets and systems. Type-2 fuzzy systems offer the ability to model and reason with uncertain concepts. When faced with uncertainties type-2 fuzzy systems should, theoretically, give an increase in performance over type-l fuzzy systems. However, …
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Design Optimization of Fuzzy Logic Systems
Fuzzy logic systems are widely used for control, system identification, and pattern recognition problems. In order to maximize their performance, it is often necessary to undertake a design optimization process in which the adjustable parameters defining a particular fuzzy system are tuned to …
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Learning of Type-2 Fuzzy Logic Systems using Simulated Annealing.
… simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of type-1 and type-2 fuzzy logic systems to maximise their modelling ability. …
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Improving risk-adjusted performance in high-frequency trading: The role of fuzzy logic systems
… trading performance of the proposed fuzzy logic models. We show that applying risk-return objective functions and accounting for transaction costs improve out-of-sample results. Our experiments identify that neuro-fuzzy models exhibit superior performance stability across multiple …
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Neural Fuzzy Techniques in Vehicle Acoustic Signal Classification
… considered: multilayer perceptrons and adaptive fuzzy logic systems. A multilayer perceptron is a network inspired by biological neural systems. Even though it is far from a biological system, it possesses the capability to solve many interesting problems in variety fields. Fuzzy logic systems, …
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Type-2 Fuzzy Probabilistic System for Proactive Monitoring of Uncertain Data-intensive Seasonal Time Series
This research realises a type-2 fuzzy probabilistic system for proactive monitoring of uncertain data-intensive seasonal time series in both theoretical and practical implications. In this thesis, a new form of representation, J˜-plane, is proposed for concave and unnormalized type-2 fuzzy events …
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Type-2 Fuzzy Probabilistic System for Proactive Monitoring of Uncertain Data-intensive Seasonal Time Series
This research realises a type-2 fuzzy probabilistic system for proactive monitoring of uncertain data-intensive time series in both theoretical and practical implications. In this thesis, a new form of representation, J-plane, is proposed for concave and un-normalized type-2 events as well as …
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Exploration of Emotion Modelling Through Fuzzy Logic
… with the exploration of representing psychologically grounded theories of emotion through fuzzy logic systems. It presents an introduction to the specific goals of the project, followed by an overview of the wider, multi-disciplinary field of emotion representation. Two emotion theories are …
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Intelligent autopilots for ships
The design of automatic systems for steering a ship presents difficult challenges because of their dynamic properties which vary considerably within the range of sailing conditions. Automatic steering of ships has its origin at the beginning of the century and was prompted by the introduction of …
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A transputer based prototype for a fuzzy logic controller with tuning and simulation capabilities
… for streamlining development and maintenance of fuzzy logic systems applied to industrial control. That method provides for tuning the rules and parameters for fuzzy control of an industrial process, without interfering in the production process itself. The capability to simulate a real-world …
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Application of Kalman Filtering to Real-time Flight Regime Recognition Algorithms in a Helicopter Health and Usage Monitoring System
… damage identification include neural networks, fuzzy logic systems, and Kalman filters. Recent research indicates that only the neural network approach has been applied to FRR algorithms, and that a Hidden Markov Model (HMM) approach outperformed the neural network. Additionally, public domain …
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Adaptively prestressed concrete structures
… for state identification. Adaptive control systems cannot be designed with conventional control algorithms. New control decision systems such as neural nets, expert systems, and fuzzy logic systems are needed for this task. Here, these systems are presented in general as forms of adaptive …
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Compensation of nonlinear distortion in RF amplifiers for mobile communications
… the Wiener models, and artificial intelligence systems. For predistortion feedback, feedforward and digital predistortion techniques are used. Among digital predistortion methods there are artificial intelligence systems, used in this thesis for linearization of power amplifier. This thesis …
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Parameter identification for vector controlled induction motor drives using artificial neural networks and fuzzy principles
… results using artificial neural networks and fuzzy logic systems. The thesis focuses mainly on identifying the rotor resistance, which is the most critical parameter for RFOC. Limitations of PI and fuzzy logic based estimators were identified. Artificial neural network based estimators were …
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Generic Adaptive Handoff Algorithms Using Fuzzy Logic and Neural Networks
… and Quality of Service (QoS) of cellular systems. This research presents novel approaches for the design of high performance handoff algorithms that exploit attractive features of several existing algorithms, provide adaptation to dynamic cellular environment, and allow systematic …
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A Big Bang Big Crunch Type-2 Fuzzy Logic System for Machine Vision-Based Event Detection and Summarization in Real-world Ambient Assisted Living
… occupied by various users. Machine vision based systems can help detect and summarize important information which cannot be detected by any other sensor; for example, how much water a candidate drank and whether or not they had something to eat. However, conventional non-fuzzy based methods are …
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An Explainable Artificial Intelligence Approach Based on Deep Type-2 Fuzzy Logic System
Artificial intelligence (AI) systems have benefitted from the easy availability of computing power and the rapid increase in the quantity and quality of data which has led to the widespread adoption of AI techniques across a wide variety of fields. However, the use of complex (or Black box) AI …
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A Fuzzy Logic-Based System for Soccer Video Scenes Classification
… need to have light weight video classification systems working in real time with massive data sizes. In this thesis, we introduce a novel system based on Interval Type-2 Fuzzy Logic Classification Systems (IT2FLCS) whose parameters are optimized by the Big Bang–Big Crunch (BB-BC) algorithm, …