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Figure 5 System model for fuzzy logic-based spectrum sensing.
Our system benefits from a fuzzy clustering model for fuzzy data to facilitate case retrieval and reduce the time complexity.
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On one hand, to capture linguistic information, Yu [18] employed an absolute term linearization technique and a fuzzy rating expression into a GP-AHP model for solving fuzzy AHP problems.
A genetic algorithm is designed to solve the general maximum entropy model for discrete fuzzy variables, which is illustrated by some numerical experiments.
In this work, the adaptive neuro-fuzzy inference system (ANFIS) approach is used for the speed and the exhaust temperature control of the gas turbine, where an automatic model for the fuzzy rule generation is use.
Then, an event-based filter design model for T S fuzzy systems is constructed by taking the effect of event-triggered scheme and the sensor faults into consideration.
The variable x i j k ( p ) represents the unknown quantity to be transported from origin a i ( p ) to destination b j ( p ) by means of k th conveyance for item p = 1, 2, …, T. Then we propose the mathematical model for the fuzzy inequality constraint.
First, the Takagi Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the uncertain nonlinear system.
The Takagi Sugeno is a famous fuzzy inference model for data-based fuzzy modeling (Michael 2005).
Fig. 4 Three-dimensional model of fuzzy logic for steering a data rate.
The results show that the proposed method can provide optimal model structure and parameters for fuzzy modeling, possesses high learning efficiency, and is smoother than CART algorithm.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com