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Showing 1 to 10 of 10 for “"defuzzification"”.
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Type-2 Fuzzy Logic: Circumventing the Defuzzification Bottleneck
… 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 computational complexity derives from the enormous number of embedded sets …
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Implementing adaptive fuzzy logic controllers with neural networks.
… membership functions, inference procedures, and defuzzification algorithms of fuzzy control systems; generate new fuzzy control rules so that fuzzy control systems can adapt to gradual changes in environments and implement parallel execution of rule matching, firing, and defuzzification. Several …
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A fuzzy logic-based text classification method for social media
… number of fuzzy rules are designed and different defuzzification methods are combined in order to obtain desired classification results. This work compares the proposed method with the well-known keyword search method in terms of correctness rate and quantity. The result shows that the proposed …
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Dealing With Uncertainty in Engineering and Management Practices
… and a fuzzy goal. The solution includes a defuzzification process and a crisping process. An alpha-cut technique is utilized for the defuzzification process, and an interval linear programming algorithm is used to the crisping process. One mixed technique (links the alpha-cut technique and …
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Monotonicity aspects of linguistic fuzzy models
… models applying the Center of Gravity defuzzification method and using fuzzy output partitions of trapezial membership functions, (2) presenting a new performance measure for fuzzy ordered classifiers, referred to as the average deviation (AD) as it takes the ordering of the output …
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Neuro-Fuzzy Based Intelligent Approaches to Nonlinear System Identification and Forecasting
… (AFLS) model which incorporates a prototype defuzzification scheme, while utilising an efficient, compared to the Takagi–Sugeno–Kang (TSK) based systems, fuzzification layer has been developed for the detection of meat spoilage using Fourier transform infrared (FTIR) spectroscopy. The …
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System identification and control of magnetic bearing systems
… t-norm and s-norm operations, and different defuzzification were investigated. To further improve system performance, scaling factors were tuned. Again, simulations showed highly promising results. Comparative studies between the conventional and advanced fuzzy control methods were also …
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Temporal logic-based fuzzy decision support system for diagnosis of rheumatic fever and rheumatic heart disease
… and ARF. The Fuzzification, Fuzzy Inferences and Defuzzification components are applied to design and implement a Fuzzy Model. The research undertaken divided the overall ARF diagnosis problem, in effect its requirements, into several sub-problems and each model of the Hybrid Approach addressed …
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A Comparison of Methods to Construct an Optimal Membership Function in a Fuzzy Database System
A fuzzy set is one in which membership in a category is not Boolean, rather items have a degree of membership. Fuzzy databases expand on this idea by storing fuzzy data and allowing data to be retrieved based on its degree of membership. Determining the degree of membership that satisfies the …
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Neural Fuzzy Techniques in Vehicle Acoustic Signal Classification
Vehicle acoustic signals have long been considered as unwanted traffic noise. In this research acoustic signals generated by each vehicle will be used to detect its presence and classify its type. Circular arrays of microphones were designed and built to detect desired signals and suppress unwanted …