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- To make perdition in an effective way, power load forecasting model based on BP neural network is established. 在此基础上,为了对河北省南部电网月用电量进行有效的预测,建立了BP神经网络的负荷预测模型。
- According to the trait of power load, this paper proposes a PSO based fuzzy neural network model for short-term load forecasting. 摘要针对短期负荷预测的特点，提出基于粒子群(PSO)优化的模糊神经网络短期负荷预测模型。
- The selection of the modeling data, data's pretreatment of power load forecasting and their effects on forecasting precision are discussed mainly. 摘要著重论述了电力负荷预测中建模数据的选择、预处理方法及其对预测精度的影响。
- Theory analysis and example calculation both manifest the high accuracy of the model,it is fit for the wide use in the power load forecasting. 理论分析和实例计算均表明该预测模型的精确度较高,适合在电力负荷预报中推广应用。
- 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。
- The durability of non-linear power load is researched and short-term load forecasting is performed in durability span by fractal interpolation algorithm. 讨论了非线性电力负荷持久性问题,并在持久性区间利用分形插值算法进行了短期负荷预测。
- Proceed from the local actual conditions of Fuxin electrified wire netting in motion, this text developed the relevant application software of electric power load forecasting. 本文以电力系统的实时数据为主要的时间序列研究对象,针对阜新地区电网运行实际,开发了相应的电力负荷预测应用软件。
- For a multifactor power load prediction problem and typical training sample selection, a new method for Short-Term Load Forecasting (STLF) based on data mining is put forward. 针对电力负荷受到多因素的影响以及典型训练样本选择问题,提出了一种基于数据挖掘技术的新型短期负荷预测方法。
- SONG Chao,HUANG Min-xiang,YE Jian-bin.The application and problems of wavelets used in short-term power load forecasting [J ].Proceedirgs of the EPSA,2002, 14(3) :8-12. [4]宋超;黄民翔;叶剑斌.;小波分析方法在电力系统短期负荷预测中的应用[J]
- SONG Chao,HUANG Min-xiang,YE Jian-bin.The application and problems of wavelets used in short-term power load forecasting[J].Proceedings of the EPSA,2002,14(3):8-12. [1]宋超;黄民翔;叶剑斌.;小波分析方法在电力系统短期负荷预测中的应用[J]
- For a multifactor power load prediction problem, this paper attempts to propose anew method for Short-Term Load Forecasting (STLF), by combining rough set and artificialneural network. 针对电力系统多因素负荷预测问题的复杂性,融合粗糙集方法与遗传神经网络各自优势,提出一种新型的短期负荷预测方法。
- In the time sequence the trend component and periodical component were considered to make the load forecasting model more coincident with the features of power loads. 同时，时间序列考虑了趋势分量和周期分量，使负荷预测模型更加符合电力负荷特性。
- The GRNN-MDE,which is based on DE and provides powerful capacity in non-linear modeling and predicting,is applied to modeling short-term power load forecasting,and the result is satisfied. 以推广能力作为优化目标,所建的GRNN有很强的非线性拟合能力和优良的预报性能,将其成功地为短期电力负荷预测建模,获得了满意的预测结果。
- Medium and long term power load forecasting 中长期电力负荷预测
- med-long term power load forecasting 中长期电力负荷预测
- Short-term power load forecasting 短期电力负荷预测
- mid-long term power load forecast 中长期电力负荷预测
- Application of Group Data Handling Method in Power Load Forecasting 数据处理组合方法在电力负荷预测中的应用
- Application of chaotic time series theory in power load forecasting 混沌时序建模的理论在电力负荷预测中的应用
- New Approach of Long and Medium Term Power Load Forecasting 中长期电力负荷预测中的新思路
