This paper presents a predictive coding model based on adaptive neuro-fuzzy inference system (ANFIS).
提出了一种利用神经模糊推理系统（ANFIS）构建预测器的图像压缩预测编码算法。
Medical Diagnosis; Machine Learning; Back-Propagation Neural Network; Adaptive Neural Fuzzy Inference System.
医学诊断；机器学习；倒传递网路；适应性类神经模糊推论系统。
The application of Subtractive Clustering Fuzzy Inference System model to forecast short-term load is presented.
采用减法聚类辅助模糊推理系统进行电力系统短期负荷预测。
A sorting method with Fuzzy Inference System (FIS) feature fusion is designed to improve the robustness of iris recognition.
排序方法模糊推理系统(FIS)特征融合的目的是为了提高虹膜识别的鲁棒性。
Noise canceling by using fuzzy inference system is studied. A kind of nonlinear noise cancellation algorithm based on T-S fuzzy model is proposed.
对模糊推理系统在噪声消除中的应用进行了研究，提出了一种基于T - S模糊模型的模糊非线性噪声消除算法。
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。
The model is used to perform the numerical simulation of slope stable state, to acquire the data for adaptive neuro-fuzzy inference system(ANFIS) analysis.
同时基于自适应神经模糊推理系统建立了岩体力学参数与边坡抗滑力和下滑力的映射模型，分析得到抗滑力和下滑力的统计特征。
Then two different fuzzy systems are designed to approximate the direct model and the inverse one on the basis of adaptive neuro-fuzzy inference system(ANFIS).
根据自适应神经模糊推理系统原理，设计两个模糊系统分别逼近磁流变阻尼器的正模型和逆模型。
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。
Adaptive neural fuzzy inference system (ANFIS), as a local approximation approach, could be used to model the quantitative structure-activity relationship (QSAR) of medicine.
作为一种局部逼近方法，自适应神经模糊推理系统(ANFIS)适于为药物定量构效关系(QSAR)建模。
In this paper, we propose a fuzzy reinforcement algorithm, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.
论文提出一种模糊强化学习算法，通过模糊推理系统将连续的状态空间映射到连续的动作空间，然后通过学习得到一个完整的规则库。
This paper gives the simulation example for modeling a typical system with Adaptive Neural-Fuzzy Inference system and expatiates the method for choosing these three parameters.
该文应用自适应神经网络模糊推理系统的方法对一个典型系统进行建模仿真，并阐述这三个参数的寻优方法。
ANFIS (Adaptive Neural Fuzzy Inference System) is first presented to obtain the global load model for describing the nonlinear characteristics of the electric load in the paper.
首次提出了采用自适应神经模糊推理系统(ANFIS)建立全局负荷模型，描述电力负荷的非线性、变结构特性。
A fuzzy Q learning algorithm is proposed in this dissertation, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.
首先，提出一种模糊Q学习算法，通过模糊推理系统将连续的状态空间映射到连续的动作空间，然后通过学习得到一个完整的规则库。
A novel hybrid neural fuzzy inference system is presented. Only based on the desired input output data pairs, are the knowledge acquisition and initial fuzzy rule sets available.
设计一种新型混合模糊神经推理系统，该系统仅从期望输入输出数据集即可达到获取知识、确定模糊初始规则基的目的。
Proposed an adaptive network fuzzy inference system control strategy based on hierarchy structure of gait planning, which do not require detailed kinematics or dynamic biped models.
提出一种基于步态规划分级结构的自适应网络模糊推理系统控制策略，该方法不需要确定双足机器人运动学和动力学模型。
Aiming at the problem of guided bombs in low precision, this paper presents a kind of intelligence control system of guided bomb based on Adaptive Neuro-Fuzzy Inference system (ANFIS).
针对目前制导炸弹命中精度低的问题，提出一种基于自适应神经模糊推理系统(ANFIS)的制导炸弹智能控制系统。
In this paper, we present an Adaptive Network-based fuzzy Inference system (ANFIS), based on a neuro-fuzzy controller, as a possible control mechanism for a ship stabilizing fin system.
提出基于自适应网络模糊推理系统(ANFIS)的神经模糊控制器作为船舶减摇鳍系统的控制装置。
The subsidence of the indoor model test is also predicted with this theory. The observed data are compared with the predicted data with the adaptive neuro-fuzzy inference system (ANFIS).
对室内模型试验进行沉降预测，并和实验观测数据以及自适应神经网络系统(ANFIS)预测结果进行了比较。
Due to the function equivalence between RBF neural networks and fuzzy inference system, fuzzy experience method is adopted to select the centers and the numb er of basis function networks.
由于RBF网络和模糊推理系统具有函数等价性，采用模糊经验值方法选取网络中心值和基函数数目。
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。
Simulation results show that the induction motor vector control system with adaptive neuro-fuzzy inference system can improve the static and dynamic performance of the motor and has good robust.
仿真实验结果表明，具有自适应神经网络的模糊推理系统控制的异步电机矢量控制系统不仅动态和稳态性能都得到提高，而且具有较强的鲁棒性。
An approach that can effectively solve the inherent highly nonlinear dynamics problem of magnetorheological (MR) damper is proposed by using adaptive neuro-fuzzy inference system (ANFIS) technique.
提出一种利用自适应神经模糊推理系统(ANF IS)技术有效解决磁流变(MR)阻尼器所固有的高度非线性动特性问题的方法。
The key technology of design fuzzy logic detector for PIO events is the choice of fuzzy variables and design of fuzzy inference system, and fuzzy variables are described by some membership functions.
设计模糊逻辑探测器模型用于PIO探测关键在于模糊变量的选取与模糊推理的设计，模糊变量是由若干隶属函数描述的。
Using these means, we have developed an expert system for the design of slew ring with capacity of fuzzy inference SRBES.
运用这一手段，我们开发成功了具有模糊推理能力的回转支承设计专家系统SRBES。
Aim at the problem of multi-sensors target tracking in the dual band IR imaging system, a method of target tracking is presented using adaptive weighting fusion based on fuzzy inference.
针对双色红外成像制导系统中多传感器目标跟踪的实际问题，提出了一种基于模糊推理自适应加权融合的目标跟踪算法。
A binary input output FAM system is built as an inference engine with parallel fuzzy inference.
建立了基于二值输入输出模糊联想系统的并行模糊推理机制。
A binary input output FAM system is built as an inference engine with parallel fuzzy inference.
建立了基于二值输入输出模糊联想系统的并行模糊推理机制。
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