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Showing 1 to 20 of 24 for “"type-2 fuzzy"”.
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Type-2 Fuzzy Alpha-cuts
Systems that utilise type-2 fuzzy sets to handle uncertainty have not been implemented in real world applications unlike the astonishing number of applications involving standard fuzzy sets. The main reason behind this is the complex mathematical nature of type-2 fuzzy sets which is the source of …
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A study of type-2 fuzzy clustering
Fuzzy C-means (FCM) has been a prominent clustering algorithm for a long time. It was extended to a type-2 framework by the linguistic fuzzy C-means (LFCM) algorithm that operates on vectors of fuzzy numbers utilizing the extension principle, the decomposition theorem, and interval analyses. The …
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Type-2 Fuzzy Logic: Circumventing the Defuzzification Bottleneck
Type-2 fuzzy inferencing for generalised, discretised type-2 fuzzy sets has been impeded by the computational complexity of the defuzzification stage of the fuzzy inferencing system. Indeed this stage is so complex computationally that it has come to be known as the defuzzification bottleneck. The …
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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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An Explainable Artificial Intelligence Approach Based on Deep Type-2 Fuzzy Logic System
… there might be a large number of features. This type of explanation is useful for tasks such as image recognition, but in other tasks, it might be hard to distinguish the most important features. Second, Model induction, which involves methods that are model agnostic, but these methods might not …
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A type-2 fuzzy logic based goal-driven simulation for optimising field service delivery
… to reduce the gaps mentioned above by exploiting fuzzy logic capabilities such as mimicking human thinking and handling uncertainty. Moreover, this thesis also finds support in the Explainable AI field, particularly in the strategies and characteristics to deploy more transparent intelligent …
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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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Analysis and Applications of the Km Algorithm in Type-2 Fuzzy Logic Control and Decision Making
Interval type-2 (IT2) fuzzy logic controller (FLC) is an extension of type-1 (T1) FLC. A large number of experiments have demonstrated that the IT2 FLC can produce more satisfactory performance. However, there has been no rigorous theoretical analysis studying the potential advantage of the IT2 …
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Many-Objective Genetic Type-2 Fuzzy Logic Based Workforce Optimisation Strategies for Large Scale Organisational Design
… be presented. The system will employ interval type-2 fuzzy logic to handle the uncertainties with the real-world data, such as travel times and task completion times. The proposed system was developed with data from British Telecom (BT) and was deployed within the organisation. The techniques …
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Type-2 Fuzzy Logic based Systems for Adaptive Learning and Teaching within Intelligent E-Learning Environments
… of teaching Excel and PowerPoint in which the type 2 system is learnt and adapted to student and teacher behaviour. The type-2 fuzzy system will be subjected to extended and varied knowledge, engagement, needs, and a high level of uncertainty variation in e-learning environments outperforming …
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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
… had something to eat. However, conventional non-fuzzy based methods are not robust enough to recognize the various complex types of behaviour in AAL applications. Fuzzy logic system (FLS) is an established field of research to robustly handle uncertainties in complicated real-world problems. In …
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Geometric Fuzzy Logic Systems
… increase 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. …
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Stochastic Search and Fuzzy Modelling for Real World Complex Systems
… the goal was to discover whether Interval Type-2 Fuzzy Logic was an appropriate choice to represent the intrinsic uncertainty present in a large Supply Chain operation. Stochastic search algorithms were used with a series of Interval Type-2 Fuzzy Logic models to identify suitable inventory …
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Intelligent control of a class of nonlinear systems
… of this study is to improve and propose new fuzzy control algorithms for a class of nonlinear systems. In order to achieve the objectives, novel stability theorems as well as modeling techniques are also investigated. Fuzzy controllers in this work are designed based on the fuzzy basis …
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Fuzzy Decision Support Applied to Machine Maintenance
… of real world data leads to the use of type-1 fuzzy sets, type-2 fuzzy sets, fuzzy decision tree and fuzzy time-series for fuzzy data-mining - to which they are applied for the look-ahead based interval-valued fuzzy decision tree with optimal perimeter of the neighbourhood (LAIVFDT-OPN) …
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Exploration of Emotion Modelling Through Fuzzy Logic
… 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 explored in detail. One, rooted in …
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Support Vector Machine-based Fuzzy Systems for Quantitative Prediction of Peptide Binding Affinity
… real-value predictive models through the use of fuzzy systems. A non-linear system is proposed with the aid of support vector-based regression to improve the fuzzy system and applied to the real value prediction of degree of peptide binding. This research study introduced two novel methods to …
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An Extended Fuzzy Discrete Event System For Hiv/aids Treatment Regimen Selection
… appeared in literature that utilized theory of fuzzy discrete event system (FDES) to capture the meaning of experts' knowledge; a form of consensus involving estimated points and type-1 fuzzy sets. The goal was to assign exact matching regimens as close as possible to those regimens preferred by …
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A Fuzzy Logic-Based System for Soccer Video Scenes Classification
… 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, which allows for the automatic scenes classification using optimized rules in broadcasted soccer matches video. The …
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