Description: 一个线性神经元网络程序，且记录了训练过程的，能看到网络训练的具体情况，以及权值的变化-a linear neural network program, which records the training process, which would see the specific network training, and the change of power Platform: |
Size: 3072 |
Author:brezze |
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Description: 本文分析小波神经网络的特点重点研究在电力负荷预测中连续小波神经网络与BP神经网络相比具有的优缺点对认识和应用小波神经网络具有重要意义算例表明在网络结构相同的情况下连续小波神经网络比BP神经网络具有更高的预测精度-wavelet analysis of this neural network research focused on the characteristics of the power load forecasting continuous wavelet neural network and BP Neural networks have their advantages and disadvantages compared to the understanding and application of wavelet neural networks is of great significance example shows the network structure with the continuous wavelet neural network than BP neural network has a higher accuracy of prediction Platform: |
Size: 55296 |
Author:bluebowl |
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Description: 故障诊断 基于BP神经网络的故障诊断系统 1生成BP网络2.训练和自适应调整-Fault diagnosis based on BP neural network fault diagnosis system for a generation of BP network 2. Training and adaptive adjustment Platform: |
Size: 1024 |
Author:范范 |
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Description: 基于Elman神经网络的预测程序，可用于电力系统短期负荷预测 -Elman neural network-based forecasting process, can be used for short-term load forecasting of power system Platform: |
Size: 1024 |
Author:liu |
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Description: 可用于电力系统短期负荷预测的RBF神经网络程序-Power system can be used for short-term load forecasting procedures of the RBF neural network Platform: |
Size: 1024 |
Author:liu |
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Description: 本文首先介绍了有源电力滤波器的基本结构和工作原理，并对一些常规的谐波电流检测方法的优缺点进行了比较。其次，针对传统的谐波电流检测方法的缺陷，提出将神经网络与基于噪声抵消原理的自适应谐波检测相结合，利用径向基函数运算量小、收敛快、无局部极小值等优点，构造了一种基于径向基函数神经网络的谐波电流检测方法，仿真结果表明该检测方法具有很好的动态响应及畸变电流检测精度。最后，设计了一套实验系统，对本文所采用的系统方案进行了实验验证。仿真表明，本文所采用的有源电力滤波器检测系统方案切实可行，能够较好地实现动态检测谐波和无功功率的目的。 -This paper, firstly, introduces the basic structure and principle of APF, and then makes comparison among some conventional harmonics detections methods. Secondly, contraposes the limitation of the traditional harmonic current detecting method based on neural network, presents the method that combines the neural network and auto adaptive harmonic current detecting method based on the principle of noise each other eliminating.As the characteristics that are small calculative quantity, fast converge, without local minimal point of Redial Basis Function (RBF), this dissertation forms a new harmonic current detecting method based on RBF. The simulation results show that the method has many advantages, such as good dynamic response, high accuracy. At last, A system is designed to verify the proposed APF scheme .The results of simulation show that the proposed APF scheme is practical and can detect harmonics and reactive power effectively. Platform: |
Size: 1900544 |
Author:ＭＣ |
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Description: This paper proposes a fault location method employing wavelet fuzzy neural network to use post-fault transient and steady-state measurements.
When single line to ground fault (SLG) occurs in the distribution lines of an industrial system, the transient feature is distinct
and the high frequency components in the transients can be employed to reveal fault characteristics. In this paper, wavelet transform is
applied to extract fault characteristics from the fault signals. Fuzzy theory and neural network are employed to fuzzify the extracted
information. Wavelet is then integrated with fuzzy neural network to form the wavelet fuzzy neural network (WFNN). The WFNN
is most suitable for post-fault transient and steady-state signal analysis in industrial distribution power system. Analysis and simulation
results illustrate that the theory and algorithm of the WFNN proposed in this paper are efficient in fault location. The WFNN can be
widely applied in fault analysis of power system.-Application of wavelet fuzzy neural network in locating single line
to ground fault (SLG) in distribution lines Platform: |
Size: 227328 |
Author:charlie |
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Description: These set of programs are written to design a robust power system stabilizer for minimizing the effects of low frequency oscillations in electric power systems. A complete nonlinear model of the power system represented by a single machine connected to an infinite bus is developed in the Simulink environment. A fuzzy Power System Stabilizer is designed using the fuzzy logic toolbox of matlab and its parameters are tuned by a NEural Network controller. Platform: |
Size: 15360 |
Author:al-amin |
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Description: 文章展示了一种新的方法用于功率系统中短期负载预测。提出的方案使用混沌时间序列分析基于确定性混沌去捕捉复杂的负载行为特征。确定性的混沌允许我们重构一个时间序列并决定输入的变量个数。这篇文章描述了混沌时间序列对日间功率系统峰值的分析。确定性混沌的非线性图形通过多层感知器的神经网络得到。提出的方案在一个例子中具体阐述。-This paper presents a new approach to short-term load forecasting in power systems. The proposed method makes use of chaos time series analysis that is based on deterministic chaos to capture characteristics of complicated load behavior. Deterministic chaos allows us to reconstruct a time series and determine the number of input variables. This paper describes chaos time series analysis of daily power system peak loads. The nonlinear
mapping of deterministic chaos is identified by the multilayer perceptron of an artificial neural network. The proposed approach is demonstrated in an example. Platform: |
Size: 382976 |
Author:will |
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Description: 径向函数神经网络的三种算法,里面是一维输入，一维输出，很容易推广到多维，拟合的效果很好-Radial basis function neural network for power system load-flow Platform: |
Size: 14336 |
Author:lan |
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Description: Elman神经网络的数据预测—电力负荷预测模型研究 教学代码-Elman neural network data to predict- the power load forecasting model for teaching code Platform: |
Size: 2048 |
Author:mars |
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Description: 神经网络的数据预测—电力负荷预测模型研究,带有数据，调 试过，可以运行，希望对大家有帮助-Neural network data prediction- the power load forecasting model with data, debugging, you can run, and I hope for all of us to help Platform: |
Size: 2048 |
Author:张力 |
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Description: 运用神经网络与时间序列分析对风电功率进行预测的一个matlab程序。-Using neural network and time series analysis forecast wind power Platform: |
Size: 41984 |
Author:年兴 |
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Description: 基于人工神经网络法的风电功率预测matlab程序，可预测未来几十个小时内的风电功率。-Based on Artificial Neural Network Method wind power prediction matlab program, you can predict the future of dozens of hours of wind power. Platform: |
Size: 15360 |
Author:yunhai |
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Description: 这是一个四个不同的S函数实现集合的递归模糊神经网络（RFNN）。该网络采用了4组可调参数,这使得它非常适合在线学习/操作，从而可应用到系统识别等方面。-This is a collection of four different S-function implementations of the recurrent fuzzy neural network (RFNN) described in detail in [1]. It is a four-layer, neuro-fuzzy network trained exclusively by error backpropagation at layers 2 and 4. The network employs 4 sets of adjustable parameters. In Layer 2: mean[i,j], sigma[i,j] and Theta[i,j] and in Layer 4: Weights w4[m,j]. The network uses considerably less adjustable parameters than ANFIS/CANFIS and therefore, its training is generally faster. This makes it ideal for on-line learning/operation. Also, its approximating/mapping power is increased due to the employment of dynamic elements within Layer 2. Scatter-type and Grid-type methods are selected for input space partitioning. Platform: |
Size: 117760 |
Author:林真天 |
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Description: BP神经网络预测风电场功率，利用BP神经网络对风电场未来48小时内的功率进行预测-Wind power prediction for wind farm with BP neural network Platform: |
Size: 123904 |
Author:Kenny |
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Description: 本程序将神经网络训练的算法应用于电力系统的负荷预测，适应性强，结果准确-This program will train the neural network algorithm is applied to the power system load forecasting, adaptable, accurate Platform: |
Size: 134144 |
Author:wangjinxing |
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