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基于BP神经网络电力系统短期负荷预测的R实现

于 2018-06-27 发布文件大小:5659KB

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下载积分: 1 下载次数: 25

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代码说明：

基于BP神经网络的R实现，改进了BP神经网络，可运行。(R implementation based on BP neural network)

文件列表：

electric, 0 , 2017-11-21
electric\20150104.png, 3972 , 2017-11-21
electric\20150105.png, 3614 , 2017-11-21
electric\20150106.png, 3733 , 2017-11-21
electric\20150107.png, 3787 , 2017-11-21
electric\20150108.png, 3824 , 2017-11-21
electric\20150109.png, 3810 , 2017-11-21
electric\20150110.png, 3684 , 2017-11-21
electric\code.txt, 1228 , 2017-11-21
electric\predict.csv, 12175 , 2017-11-21
electric\shuchu.csv, 1259955 , 2017-06-19
electric\shuru.csv, 33598 , 2017-06-19
electric\实验指导书.docx, 70180 , 2017-11-21
electric\问题原型, 0 , 2017-11-21
electric\问题原型\A题电力系统短期负荷预测.pdf, 226130 , 2016-05-26
electric\问题原型\附件1-数据.xlsx, 4976784 , 2016-05-17

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数学建模之公园建路问题（2012年西北工业大学数学建模竞赛）(Mathematical modeling of the park was built Northwestern Polytechnical University Mathematical Contest in Modeling (2012))

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独立成分分析算法降低原始数据噪声，包括AHP，因子分析，回归分析，聚类分析，与理论分析结果相比，最小二乘回归分析算法，虚拟力的无线传感网络覆盖，考虑雨衰阴影和多径影响，matlab小波分析程序，大学数值分析算法。( Independent component analysis algorithm reduces the raw data noise, Including AHP, factor analysis, regression analysis, cluster analysis, Compared with the results of theoretical analysis, Least-squares regression analysis algorithm, Virtual power wireless sensor network coverage, Consider shadow rain attenuation and multipath effects matlab wavelet analysis program, University of numerical analysis algorithms.)

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