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rbf
相关语句
  径向基
    Nonlinear Temperature Modeling and Prediction of MCFC Based on RBF Neural Networks
    基于径向基函数神经网络的燃料电池温度非线性建模与预测
短句来源
    DIRECT CONTROL OF CURRENTS BASED ON ADAPTIVE RBF NEURAL NETWORK FOR BRUSHLESS DC MOTORS
    基于自适应径向基函数神经网络的无刷直流电机直接电流控制
短句来源
    GENERALIZED GROWING AND PRUNING RBF NEURAL NETWORK BASED HARMONIC SOURCE MODELING
    基于广义生长-剪枝径向基函数神经网络的谐波源建模
短句来源
    A SHORT-TERM LOAD FORECASTING APPROACH BASED ON IMMUNE CLUSTERING RBF NETWORK MODEL
    基于免疫聚类径向基函数网络模型的短期负荷预测
短句来源
    THE CALCULATION OF ENERGY LOSSES IN DISTRIBUTION SYSTEMS BASED ON RBF NETWORK WITH DYNAMIC CLUSTERING ALGORITHM
    基于动态聚类算法径向基函数网络的配电网线损计算
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  “rbf”译为未确定词的双语例句
    ELECTRIC LOAD-FORECASTING USING RBF NEURAL NETWORKS
    RBF神经网络在电力负荷预测中的应用
短句来源
    To eliminate the influence of initial weights values of neural networks on controllers, a RBF neural network controller optimized by a new improved genetic algorithm (GA) is proposed.
    为了消除神经网络参数初值对控制器性能的影响,提出了一种改进遗传算法优化的RBF神经网络控制器。
短句来源
    In this article, the research and applied of BP network and RBF network as well as wavelet neural network in power load forecasting has been summarized in detail.
    详细综述了BP网络、RBF网络以及小波神经网络在电力负荷预测领域的研究和应用现状。
短句来源
    On the T-S Fuzzy RBF Network Multi-variable Adaptive Controller
    T-S型模糊RBF神经网络多变量自适应控制器的研究
短句来源
    THE STUDY ON RELIABILITY ASSESSMENT OF ELECTRICAL POWER SYSTEMS USING RBF NEURAL NETWORK
    基于RBF神经网络的电网可靠性评估模型研究
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  rbf
At the same time, linear regression, nonlinear regression and radial basis function (RBF) neural network models are set up to evaluate weld quality between the selected parameters and tensile-shear strength.
      
For the RBF neural network model, which is more effective for monitoring weld quality than the others, the average error validated is 2.88% and the maximal error validated is under 10%.
      
The provision of residents of the European North of Russia with vitamin B2 (riboflavin (RBF)) and the activity of the erythrocytic RBF-dependent enzyme glutathione reductase (EC 1.6.4.2) were studied.
      
in residents of the European North of juvenile and senile age The provision with RBF showed a tendency toward a decrease as compared to other age groups of the population.
      
The parameters of provision with RBF were correlated significantly with the level of physical activity, alcohol status, and season of the year.
      
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The application of radial basis Function (RBF) ANN model to the daily peak load and daily 24-hour load in power system is proposed. The structure of the RBF network is presented first, then, the clustcr technique and orthogonal learning algorithm are used for determining the RBF network's centers and for network training. The effectiveness of the presental foreasting strategy is demonstrated by baning and triting using the data collected from Jing -Jin-Tang power network.

将RBF(RadiaBasisFunctio.辐基函数)人工神经网络模型用于电力系统日峰值负荷与日小时负荷的预测。文中首先给出了RBF网络的结构,然后讨论确定RBF网络中心及网络训练的聚类法和正文化法。利用从京津唐系统中收集到的负荷数据进行网络模型的训练和回响检测,所得结果证实了ABF网络用于负荷预测的有效性。

This paper introduces a neural network-Radial Basis Function Network for short-term load forecasting. This algorithm considers the influence of atmospheric temperature on electric load, take a n-means clustering technique to adjust the RBF centers, and use least Squares algorithm for updating the RBFN weights. The examples show that it has more significant advantages in convergence and forecasting accuracy.

本文根据电力系统短期负荷预报的特点和径向基函数神经网络的非线性辨识功能,提出了一种负荷预报的新算法-RBFN算法。该算法能够体现负荷的波动性和气候对负荷的影响,收敛速度较快,由于采用丛聚技术调整径向基函数中心,该算法具有较高的预报精度,通过对实际系统的实验表明:可用于提前24小时的电力系统负荷预报。

This paper presents a hybrid model for short term load forecasting that integrates artificial neural networks (ANN) and fuzzy expert system. Radical basis function(RBF) network is introduced and an orthogonal least square alogorithm (OLS) is used to determine RBF function centers. The initial load is forecasted by the trained RBF networks, and then, the fuzzy expert systems modify the initial load considering the possibility of load variation due to changes in temperature and the load behavior...

This paper presents a hybrid model for short term load forecasting that integrates artificial neural networks (ANN) and fuzzy expert system. Radical basis function(RBF) network is introduced and an orthogonal least square alogorithm (OLS) is used to determine RBF function centers. The initial load is forecasted by the trained RBF networks, and then, the fuzzy expert systems modify the initial load considering the possibility of load variation due to changes in temperature and the load behavior of holiday. Day types are divided into five classes in this paper. Test results show that the hybrid model can forecast load with a higher accuracy and a faster speed.

结合人工神经元网络(ANN)和模糊专家系统进行负荷预测.给出了径向基函数(RBF)网络的结构,并采用正交最小平方法(OLS)选取RBF中心.先用ANN进行基本负荷预测,然后考虑天气变化和假日因素所引起的负荷变化,利用模糊专家系统进行负荷调整.文中还把日期划分为5类.测试结果表明,该方法具有较高的精度和较快的速度.

 
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