When obtaining plenty data, self-adapt neural network fuzzy control system ANFIS come into being subjection degree function and fuzzy rule, namely come into being fuzzy controller.
当获得了足够的数据后，通过自适应神经网络模糊系统ANFIS来训练产生隶属度函数和模糊规则，即产生模糊控制器。
Applying Adaptive Neural-Fuzzy Inference System (ANFIS) can produce fuzzy rules and adjust membership functions automatically based on data without experience of experts.
自适应神经网络模糊推理系统(ANFIS)能基于数据建模，无须专家经验，自动产生模糊规则和调整隶属度函数。
A new superheated steam temperature control system design scheme is proposed, the main controller design is based on Adaptive Network-based Fuzzy Inference system (ANFIS).
提出一种新型的过热汽温控制方案，主控制器基于自适应神经网络模糊推理系统(ANFIS)进行设计。
This article utilizes the character of Gray Theory to predict the economy parameter, and then in order to obtain a better predicting effect, the ANFIS is employed to predict its simulating error.
利用灰色理论本身的特征对经济参数进行预测，并运用自适应模糊神经网络对其拟合误差进行预测，从而达到较好的预测效果。
This paper also stated the method of Adaptive Neural-Fuzzy Inference System (ANFIS) in details, which was used to analysis and testify effect of the NN-FC.
本文还详细介绍了一种用多层前向神经网络实现模糊逻辑的自适应神经网络模糊推理系统——ANFIS，并用它来分析、验证神经模糊控制的控制效果。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
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