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What's more, a neural network synthetic evaluation model with superior in self-learning ability and computing power is proposed by improving the fuzzy evaluation model.
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By improving the team.
All punctuation marks are removed to improve the fuzzy matching (i.e., hnf-3-gamma by hnf 3 gamma ).
Over the years, many different approaches in Evolutionary Fuzzy Systems have been developed for improving the behavior of fuzzy systems, either acting on the Fuzzy Rule Base Systems' elements, or by defining new approaches for the evolutionary components.
The results show: the functions of the gain fuzzy controller based on FPGA are implemented correctly, and the design is effectively simplified, and the real-time performance is improved by using the fuzzy inference lookup table.
However, introducing fuzzy logic at node-level sensing can further improve the performance by improving local sensing results.
Cheng (1998) improved the concept of ranking fuzzy numbers using fuzzy mean and fuzzy standard deviation as proposed by Lee and Li (1988).
The experiment results demonstrate that the MFs designed by the proposed method could effectively improve the accuracy, complexity and interpretability of the fuzzy model, which provide helpful information for the fuzzy modeling of BFG pipeline pressure.
The attributes reduction, by taking under consideration fuzzy function overlap, improved the overall accuracy by 4%%.
Secondly, based on the derived fuzzy dynamics of the robotic manipulator, the dynamic NF adaptive controller is developed to improve the system performance by adaptively modifying the fuzzy model parameters on-line.
The Interval Type-2 Fuzzy Logic Controller (IT2FLC) is an advanced version of Type-1 Fuzzy Logic Controller (T1FLC) that improves the control strategies by using the advantage of its footprint of uncertainty of the Fuzzy Membership Function (MF).
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