• When the knowledge rule is found in the knowledge files, T-S fuzzy inference model is applied to resolution of question.

    当在知识库中搜索到相应的知识规则后,采用T - s模糊推理模型的求解策略进行求解。

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  • On the basis of a evolving clustering method (ECM), a new modeling approach of T-S type dynamic fuzzy inference model is proposed.

    以一种进化聚类算法(ecm)为基础,提出了一种新的T - S型动态模糊推理模型的建模算法。

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  • Given the fuzzy characteristic of rainfall weather and intensity, a fuzzy inference model of rainfall distribution and intensity of satellite cloud images was proposed.

    在卫星云图降水分析中,针对降水天气和降水强度具有明显的“模糊”特性,提出了云图降水的模糊推理模型。

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  • 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。

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  • 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。

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  • A fuzzy neural network prediction control model is stated by using the logic inference performance of fuzzy control and the learning ability of neural network.

    应用模糊控制的逻辑推理性能,借助神经网络的学习能力,提出了一种模糊神经网络预测控制模型。

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  • 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.

    针对锌钡白干燥煅烧过程建模难的问题,提出了一种基于T S模型的自适应神经模糊推理系统(ANFIS)建模方法。

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  • A solution as compensating the controlled quantity by fuzzy inference is put forward in this paper to the problem of model mismatch caused by the predictive function control.

    针对预测函数控制中模型失配的影响,提出了用模糊推理对控制量进行补偿的新型预测函数控制。

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  • In the paper, the premise structure of fuzzy model is obtained by the improved fuzzy clustering. Fuzzy inference matrices are decomposed on the basis of QR decomposition.

    本文通过改进模糊聚类方法确定模糊模型的前件结构,然后对经模糊聚类得到的模糊前件推理矩阵进行QR分解。

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  • 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。

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  • In the paper, fuzzy neural network method is used to control the size accuracy in grinding process and fuzzy inference BP-network model is produced.

    采用模糊神经网络方法进行磨削加工尺寸精度的控制,给出了模糊推理BP网络模型。

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  • We build the knowledge database with this fuzzy relationship model and we present two important algorithms about the inference process of the fuzzy relationship model in this paper.

    并且,就实现基于模糊关系数据模型推理过程,给出了两个关键性的算法。

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  • Because of the existence of the indefinite factors in power load forecasting, a new load forecasting model - the fuzzy inference forecasting is presented.

    考虑到电力负荷预测问题中存在的不确定性,采用模糊推理预测方法进行负荷预测的研究。

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  • 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.

    针对纯碱碳化过程的复杂建模问题,提出基于T-S模型的自适应神经模糊推理系统(ANFIS)的建模方法。

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  • A new concept of generalized fuzzy inference and the generalized fuzzy RBF network model are presented. The generalized Lear ni ng algorithm of this network model is derived.

    在提出广义模糊推理概念的基础上,提出并分析了广义模糊径向基(rbf)神经网络模型,给出了该网络的广义学习算法。

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  • In this paper, we introduce a method of compensating for the controlled quantity with fuzzy inference to solve the problem of model mismatch caused by the predictive function control for.

    针对预测函数控制中模型失配的影响的情况,提出了用模糊推理对控制量进行补偿的解决方案。

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  • 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。

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  • 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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  • In this paper, the test model of fuzzy hypothesis for the period analysis of the runoff process over a number of years and the method of a fuzzy statistical inference are presented.

    本文提出了多年径流过程周期分析的模糊假设检验模型及模糊统计判断方法。

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  • 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。

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  • 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。

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  • 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。

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  • A direct inverse model controller of fuzzy neural network with changeable structure based on t s inference is presented in this paper and it is used to the motion control of mobile robot.

    本文提出一种基于T -S模型的变结构模糊神经网络直接逆模型控制器,并将其应用于移动机器人的运动控制中。

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  • 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。

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  • 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。

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