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随着新的数学工具小波分析的实用化为基于NN负荷预测模型性能的改善提供了理论依据对于电力系统负荷非线性时间序列的辨识在预测方法研究中应给予重视在本文所用的基于小波原理和NN融合的预测原理是具有强的非线性时间序列的辩能力由研究和仿真表明它能有效提高预测的精度-with new mathematical tools wavelet analysis based on NN into practical load forecasting model to improve the performance
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短期负荷预测对电力系统的经济和安全运行有重要作用随着人工智能技术和高深数学理论的发展,为负荷预测研究开辟了新途径和新方法电力市场竞争机制引入对负荷预测提出新要求各种随机因素对负荷预测的影响尚未取得完善研究方法据此对负荷预测的研究一直是人们研究的热点本文是根据课题组研究工作在总结的基础上重点介绍模糊集理论数据挖掘小波分析混沌理论的负荷预测研究
关键词短期负荷预测智能技术模糊集理论数据挖掘小波分析混沌理论-short-term load forecasts on the power system
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一种适用于电力系统谐波检测的类小波方法，比较实用，但对相位信息无效-A power system harmonics detection class wavelet method, more practical, but the phase information is not valid
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自适应谐波小波包应用于电力系统谐波检测的程序-Adaptive harmonic wavelet packets applied to power system harmonic detection procedures
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This paper is a brief introduction to discrete wavelet transform as digital signal-processing
technique and the application. The field of discrete wavelet transform (DWT) is an
amazingly recent one because itÌ s better than Fourier transfor
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a transmission line fault location model which is based on an Elman recurrent network
(ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with
different inception times are implemented on a 380-kV proto
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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 trans
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随着新的数学工具小波分析的实用化为基于NN负荷预测模型性能的改善提供了理论依据对于电力系统负荷非线性时间序列的辨识在预测方法研究中应给予重视在本文所用的基于小波原理和NN融合的预测原理是具有强的非线性-With the new mathematical tools of wavelet analysis into practical load forecasting model based on the performance of NN provides a theoretical basis
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本文提出了一种自动检测和电能质量扰动分类模糊专家系统。有关干扰的类型包括电压骤降，骤升，中断，切换瞬变，冲动，闪烁，谐波和缺口。据推测，在所分析的波形采样的形式提供。傅立叶变换和小波分析，利用独特的功能获得的波形一个模糊专家系统为主体的决定有关的干扰类型而设计的。仿真研究，验证了该方法的比较研究人工神经网络为基础的分类方法和该方法研究的准确性也报告，以显示该方法的优点-This paper presents a fuzzy-expert system for automated detectio
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基于小波神经网络的电力负荷预测程序，是师兄做毕业设计时候编写的 适用于电力系统及其自动化专业-Power load forecasting based on wavelet neural network program, written by the brothers to do a graduation project applies to Electric Power System and Automation
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基于小波包变换的电力系统谐波分析,对于从事该方面的研究很有帮助-Based on wavelet packet transform power system harmonic analysis, engaged in the research helpful
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MATLAB雨燕程。电力系统电压骤降信号的小波分解结果-MATLAB Swift away. Power system voltage sag signal wavelet decomposition results
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在matlab环境下的系统小波的电力系统谐波分析的M程序-In the matlab environment system of the wavelet power system harmonic analysis M program
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本论文以 DSP 和计算机为硬件平台，以小波分析和人工神经网络为理论基础，设计了基于 TMS320F2812 的数据采集模块，对故障识别方法进行了深入研究，实现了电力电缆典型故障的识别。-Based on the hardware platform of DSP system & computer and the theory of wavelet analysis & artificial neural network, this paper designs the data acquisit
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电力系统电压骤降建模程序，小波分解系数提取以及重构，图形生成-Power system voltage sag modeling program, wavelet coefficients extraction and reconstruction, graphics generation
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With the development of power systems and the
extensive application of nonlinear elements in the electricity
system, the problem of ferroresonance do harm to the network
and electricity facilities has become more prominent. Wavelet
analysis h
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基于小波变换的电力系统谐波检测与分析研究-Power system harmonic wavelet-based detection and analysis
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电力系统暂态故障的六种形式仿真，小波分析去噪，提取特征-six form of Power system transient fault, using wavelet analysis
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基于小波包BP神经网络的短期电力系统负荷预测程序-Electric power system short-term load forecasting BP wavelet packet neural network program based on
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通过实验表明小波包变换能精确地从谐波信号中分离出基波，并能根据需要分离出任意谐波信号，是一种很好的电力系统谐波分析工具。-Experiments show that wavelet packet transform can accurately isolated in harmonic signal wave, and can according to need to separate out any harmonic signals,It is a kind of very good pow
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