An extended takagi-sugeno- kang inference system (tsk+) with fuzzy interpolation and its rule base generation. Soft Computing, Nov 2017.Jie Li, Longzhi Yang, Yanpeng Qu, and Graham Sexton. An extended takagi-sugeno-kang inference system (tsk+) with fuzzy interpolation and its rule base ...
2) switched T-S formal fuzzy systems 切换T-S型模糊系统 1. Guaranteed cost control with quadratic stability for a class of switched T-S formal fuzzy systems; 一类切换T-S型模糊系统二次镇定保成本控制 更多例句>> 3) T-S fuzzy inference system T-S型模糊推理系统 1. Aiming at the ...
Takagi-Sugeno fuzzy inference system for modeling stage-discharge relationshipLohaniA.K.GoelN.K.BhatiaK.K.ingentaconnectJournal of Hydrology AmsterdamLohani AK, Goel NK, Bhatia K. 2006. Takagi-Sugeno fuzzy inference system for modeling stage-discharge relationship. Journal of Hydrol- ogy 331: 146-...
1) Takagi-Sugeno (TS) fuzzy system Takagi-Sugeno(TS)模糊系统 2) Takagi-Sugeno fuzzy system Takagi-Sugeno模糊系统 3) Takagi-Sugeno(T-S) fuzzy control system Takagi-Sugeno(T-S)模糊控制系统 4) Takagi-Sugeno fuzzy inference system Takagi-Sugeno模糊推理系统 ...
5) Sugeno inference Sugeno推理 1. The pure time delay effects of the controlled object was made up by Smith estimating controller, and the PID controller parameters were adjusted by the fuzzy controller based on Sugeno inference. 针对工业控制中大惯性、纯滞后、参数时变非线性受控对象难于控制...
1) Takagi-Sugeno 高木-关野1. On medium-term and long-term load forecasting, this paper put forward the model of medium-term and long-term load forecasting based on the Takagi-Sugeno adaptive Neural-Fuzzy inference system by integrate fuzzy theory with neural network. 针对中长期负荷预测,本文...
Recently, an intuitionistic fuzzy inference system (IFIS) of Takagi-Sugeno type has been proposed. Previous results have shown that by adding non-membership functions, the average errors may be significantly decreased compared with FISs. In this paper, we design defuzzification methods for this class...
The Takagi–Sugeno (T–S) fuzzy model is a system described by fuzzy IF–THEN rules which can give local linear representation of the nonlinear system by decomposing the whole input space into several partial fuzzy spaces and representing each output space with a linear equation. Such a model ...
针对该问题,提出了一种模糊系统联合稀疏建模新方法L2-CFS-FIS(L2-common feature selection fuzzy inference systems),从而提高模型的泛化性能和可解释性。该方法充分考虑存在于模糊规则间的公共特征信息,同时引入模型过拟合处理机制,将模糊系统建模问题转化为一个基于双正则的联合优化问题,并使用交替方向乘子(alternating ...
机译:基于先验知识的静态非线性系统Takagi-Sugeno-Kang模糊模型的识别 6. Hybrid Solution Combining Kalman Filtering with Takagi–Sugeno Fuzzy Inference System for Online Car-Following Model Calibration [O] . Mădălin-Dorin Pop, Octavian Proștean, Tudor-Mihai David, 2020 机译:混合解决方案与...