• 采用自适应神经模糊推理系统控制器参数进行优化。

    The problem of rule explosion in FNN controller is solved for multi-variable systems.

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  • 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

    The application of Subtractive Clustering Fuzzy Inference System model to forecast short-term load is presented.

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  • 基本行为模糊推理系统设计,较高级复杂行为基本行为的融合产生。

    The elementary behaviors were achieved by fuzzy reasoning scheme, and highlevel behaviors were composed of these primitive behaviors.

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  • 排序方法模糊推理系统(FIS)特征融合目的为了提高虹膜识别鲁棒性。

    A sorting method with Fuzzy Inference System (FIS) feature fusion is designed to improve the robustness of iris recognition.

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  • 分析工业X射线底片焊缝缺陷特征建立用于焊缝缺陷分类识别模糊推理系统模型

    Weld defects classification system based on fuzzy reasoning model was established, after analysis of weld defect features in X-ray films.

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  • 提出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。

    This paper presents a predictive coding model based on adaptive neuro-fuzzy inference system (ANFIS).

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  • 证明采用模糊推理系统作为设计型结构选型决策支持系统的评价模块理想的解决方案。

    The transient stability of multi-machine power systems based on structure preserving model (SPM) is considered.

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  • 为了解决常规卡尔滤波法存在不足,给出模糊推理系统卡尔曼法相结合方法

    In order to resolve the shortcomings of the traditional Kalman filtering, a new method is presented in which the fuzzy reasoning system is combined with the traditional Kalman technology.

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  • 为了解决常规卡尔滤波法存在不足给出模糊推理系统卡尔曼法相结合的方法

    In order to resolve the shortcoming of the traditional federal Kalman filtering, a new method is presented in which the fuzzy reasoning system is combined with the traditional Kalman technology.

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  • 根据自适应神经模糊推理系统原理,设计模糊系统分别逼近流变阻尼器模型逆模型

    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).

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  • 保证性能的基础上,利用训练好的模糊推理系统材料成分进行优化,减少贵重元素加入量

    The alloy composition can be optimized by the neural-fuzzy method thereby enabling them to replace the more ex-pensive noble elements with lower cost material having comparable mechanical properties.

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  • 由于RBF网络模糊推理系统具有函数等价性,采用模糊经验方法选取网络中心值和基函数数目。

    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.

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  • 提出基于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系统控制装置

    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.

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  • 提出一种新型过热控制方案,控制器基于自适应神经网络模糊推理系统(ANFIS)进行设计

    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).

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  • 该文应用自适应神经网络模糊推理系统方法一个典型系统进行建模仿真阐述三个参数的寻优方法。

    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.

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  • 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

    Adaptive neural fuzzy inference system (ANFIS), as a local approximation approach, could be used to model the quantitative structure-activity relationship (QSAR) of medicine.

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  • 针对纯碱碳化过程复杂建模问题提出基于T-S模型适应神经模糊推理系统ANFIS)的建模方法。

    The paper introduces a kind of adaptive neural-fuzzy inference systems (ANFIS) based on T-S model to deal with the modeling problem of the complex soda carbonization process.

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  • 借助于辨识过量空气系数自适应神经网络模糊推理系统(ANFIS)模型进行静态前馈控制仿真

    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.

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  • 小波分解自适应神经模糊推理系统(ANFIS)相结合方法,建立赤道太平洋海温集成预报模型

    Based on the method of wavelet decomposition combining with ANFIS, a compositive prediction model of the equatorial east Pacific sea surface temperature anomaly (SSTa) was established.

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  • 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非线性、变结构特性

    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.

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  • 模糊推理系统噪声消除中的应用进行了研究,提出基于T - S模糊模型模糊非线性噪声消除算法

    Noise canceling by using fuzzy inference system is studied. A kind of nonlinear noise cancellation algorithm based on T-S fuzzy model is proposed.

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  • 利用ANFIS学习能力模糊逻辑推理功能,建立了竖向极限承载力预测的自适应网络模糊推理系统

    Based on the strong learning ability and fuzzy logic function of ANFIS, a method for predicting vertical ultimate bearing capacity of single pile is presented.

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  • 适应神经网络模糊推理系统(ANFIS)基于数据建模,无须专家经验自动产生模糊规则调整隶属度函数

    Applying Adaptive Neural-Fuzzy Inference System (ANFIS) can produce fuzzy rules and adjust membership functions automatically based on data without experience of experts.

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  • 针对目前制导炸弹命中精度问题提出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

    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).

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  • 提出一种基于步态规划分级结构自适应网络模糊推理系统控制策略方法需要确定双足机器人运动学动力学模型

    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.

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  • 针对锌钡干燥煅烧过程建模问题提出一种基于TS模型自适应神经模糊推理系统(ANFIS)建模方法

    In order to solve the difficult modeling problem of the lithopone calcination process, this paper proposes an adaptive neural fuzzy inference systems (ANFIS) modeling method based on t s model.

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  • 模糊关系方程求解问题模糊系统极其重要研究课题之一,大部分模糊推理系统可以通过模糊关系方程实现

    The resolution problem of fuzzy relation equations (FRES) is a very important subject in fuzzy sets and systems, the majority of fuzzy inference systems can be implemented by using FERS.

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  • 同时基于自适应神经模糊推理系统建立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统计特征。

    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.

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  • 同时基于自适应神经模糊推理系统建立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统计特征。

    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.

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