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The optimal rule structure for fuzzy systems in function approximation by hybrid approach in learning process

机译：学习过程中混合逼近的模糊系统最优规则结构

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Nguyen, Thi; Gordon-Brown, Lee; Peterson, Jim;
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年度 2008
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正文语种 eng
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1. Complex fuzzy model with PSO-RLSE hybrid learning approach to function approximation [J] . Chunshien Li, Tai-Wei Chiang International journal of intelligent information and database systems . 2011,第4期

机译：基于PSO-RLSE混合学习方法的复杂模糊函数逼近模型
2. A systematic approach to a self-generating fuzzy rule-table for function approximation [J] . Pomares H., Rojas I. IEEE transactions on systems, man, and cybernetics. Part B . 2000,第3期

机译：用于函数逼近的自生成模糊规则表的系统方法
3. A systematic approach to a self-generating fuzzy rule-table forfunction approximation [J] . Pomares H., Rojas I., Ortega J., IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics . 2000,第3期

机译：一种用于函数逼近的自生成模糊规则表的系统方法
4. The Optimal Rule Structure for Fuzzy Systems in Function Approximation by Hybrid Approach in Learning Process [C] . Thi Nguyen, Lee Gordon-Brown, Jim Peterson International Conference on Computational Intelligence for Modelling Control Automation . 2008

机译：通过混合方法在学习过程中近似模糊系统的最佳规则结构
5. A proposed intelligent bandwidth management system based on Turksen's Fuzzy Function approach using reinforcement learning forecasting. [D] . Chung, Edwin. 2005

机译：提出了一种基于Turksen模糊函数方法的强化学习预测智能带宽管理系统。
6. An approach on the implementation of full batch, online and mini-batch learning on a Mamdani based neuro-fuzzy system with center-of-sets defuzzification: Analysis and evaluation about its functionality, performance, and behavior [O] . Sukey Nakasima-López, Juan R. Castro, Mauricio A. Sanchez, 2012

机译：在基于Mamdani的神经模糊系统上进行全批处理，在线和小批量学习的方法，该系统具有集中心去模糊化：有关其功能，性能和行为的分析和评估
7. Research on Intelligent Fuzzy Optimal Active and Hybrid Control Systems of Building Structures - Verification of Optimization Method on Switching Rules of Control Forces [O] . TaKagi Kousuke, Tani Akinori, Kawamura Hiroshi 2004

机译：建筑结构智能模糊最优主动混合控制系统的研究-控制力切换规则的优化方法验证
8. Learning control of inverted pendulum system by neural network driven fuzzy reasoning: The learning function of NN-driven fuzzy reasoning under changes of reasoning environment [R] . Hayashi, Isao, Nomura, Hiroyoshi, Wakami, Noboru 1991

机译：基于神经网络驱动模糊推理的倒立摆系统学习控制：推理环境变化下NN驱动模糊推理的学习功能

The optimal rule structure for fuzzy systems in function approximation by hybrid approach in learning process

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