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load_RNN

于 2020-04-12 发布
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下载积分: 1 下载次数: 9
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说明：  python 电力负荷预测，rnn版本，python环境(Python power load forecasting, RNN version, python environment)

文件列表：

load_RNN\draw_data.py, 220 , 2020-01-01
load_RNN\Figure_1.png, 262436 , 2020-01-01
load_RNN\jianmo.py, 5485 , 2020-01-01
load_RNN\log_history\2.log\events.out.tfevents.1501239969.songling-14Z970-G-AA52C, 40487138 , 2020-01-01
load_RNN\log_history\4.log\events.out.tfevents.1501239965.songling-14Z970-G-AA52C, 15118217 , 2020-01-01
load_RNN\log_history\supervisor.log\events.out.tfevents.1501241437.songling-14Z970-G-AA52C, 45075180 , 2020-01-01
load_RNN\log_history\supervisor.log\events.out.tfevents.1501244672.songling-14Z970-G-AA52C, 9007093 , 2020-01-01
load_RNN\log_history\supervisor.log\events.out.tfevents.1501244808.songling-14Z970-G-AA52C, 16140864 , 2020-01-01
load_RNN\normalize.py, 1471 , 2020-01-01
load_RNN\output\steps=1000-MAPE=0.0561.csv, 18230 , 2020-01-01
load_RNN\output\steps=1000-MAPE=0.0580.csv, 18231 , 2020-01-01
load_RNN\output\steps=1000-MAPE=0.0589.csv, 18232 , 2020-01-01
load_RNN\output\steps=10000-MAPE=0.0449.csv, 18221 , 2020-01-01
load_RNN\output\steps=10000-MAPE=0.0529, 18227 , 2020-01-01
load_RNN\output\steps=10000-MAPE=0.0542.csv, 18223 , 2020-01-01
load_RNN\output\steps=10000-MAPE=0.0555.csv, 18238 , 2020-01-01
load_RNN\output\steps=10500-MAPE=0.0462.csv, 18235 , 2020-01-01
load_RNN\output\steps=10500-MAPE=0.0566.csv, 18240 , 2020-01-01
load_RNN\output\steps=11000-MAPE=0.0465.csv, 18238 , 2020-01-01
load_RNN\output\steps=11000-MAPE=0.0564.csv, 18227 , 2020-01-01
load_RNN\output\steps=11500-MAPE=0.0502.csv, 18233 , 2020-01-01
load_RNN\output\steps=11500-MAPE=0.0550.csv, 18231 , 2020-01-01
load_RNN\output\steps=12000-MAPE=0.0495.csv, 18233 , 2020-01-01
load_RNN\output\steps=12000-MAPE=0.0535.csv, 18218 , 2020-01-01
load_RNN\output\steps=12500-MAPE=0.0514.csv, 18236 , 2020-01-01
load_RNN\output\steps=12500-MAPE=0.0578.csv, 18239 , 2020-01-01
load_RNN\output\steps=13000-MAPE=0.0531.csv, 18223 , 2020-01-01
load_RNN\output\steps=13000-MAPE=0.0557.csv, 18233 , 2020-01-01
load_RNN\output\steps=13500-MAPE=0.0519.csv, 18221 , 2020-01-01
load_RNN\output\steps=13500-MAPE=0.0594.csv, 18241 , 2020-01-01
load_RNN\output\steps=14000-MAPE=0.0529.csv, 18233 , 2020-01-01
load_RNN\output\steps=14000-MAPE=0.0587.csv, 18216 , 2020-01-01
load_RNN\output\steps=14500-MAPE=0.0538.csv, 18255 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0508.csv, 18225 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0523.csv, 18246 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0524.csv, 18227 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0530.csv, 18215 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0539.csv, 18233 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0567.csv, 18213 , 2020-01-01
load_RNN\output\steps=1500-MAPE=0.0569.csv, 18240 , 2020-01-01
load_RNN\output\steps=15000-MAPE=0.0520.csv, 18227 , 2020-01-01
load_RNN\output\steps=15000-MAPE=0.0578.csv, 18226 , 2020-01-01
load_RNN\output\steps=15500-MAPE=0.0549.csv, 18240 , 2020-01-01
load_RNN\output\steps=15500-MAPE=0.0571.csv, 18248 , 2020-01-01
load_RNN\output\steps=16000-MAPE=0.0536.csv, 18236 , 2020-01-01
load_RNN\output\steps=16000-MAPE=0.0563.csv, 18236 , 2020-01-01
load_RNN\output\steps=16500-MAPE=0.0501.csv, 18240 , 2020-01-01
load_RNN\output\steps=16500-MAPE=0.0550.csv, 18245 , 2020-01-01
load_RNN\output\steps=17000-MAPE=0.0503.csv, 18232 , 2020-01-01
load_RNN\output\steps=17000-MAPE=0.0547.csv, 18218 , 2020-01-01
load_RNN\output\steps=17500-MAPE=0.0493.csv, 18221 , 2020-01-01
load_RNN\output\steps=17500-MAPE=0.0567.csv, 18238 , 2020-01-01
load_RNN\output\steps=18000-MAPE=0.0479.csv, 18239 , 2020-01-01
load_RNN\output\steps=18000-MAPE=0.0556.csv, 18227 , 2020-01-01
load_RNN\output\steps=18500-MAPE=0.0501.csv, 18238 , 2020-01-01
load_RNN\output\steps=18500-MAPE=0.0553.csv, 18240 , 2020-01-01
load_RNN\output\steps=19000-MAPE=0.0484.csv, 18235 , 2020-01-01
load_RNN\output\steps=19000-MAPE=0.0547.csv, 18228 , 2020-01-01
load_RNN\output\steps=19500-MAPE=0.0502.csv, 18237 , 2020-01-01
load_RNN\output\steps=19500-MAPE=0.0549.csv, 18225 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0463.csv, 18226 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0487.csv, 18229 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0494.csv, 18221 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0522.csv, 18243 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0534.csv, 18228 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0564.csv, 18232 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0584.csv, 18237 , 2020-01-01
load_RNN\output\steps=2000-MAPE=0.0589.csv, 18237 , 2020-01-01
load_RNN\output\steps=20000-MAPE=0.0526.csv, 18213 , 2020-01-01
load_RNN\output\steps=2500-MAPE=0.0490.csv, 18240 , 2020-01-01
load_RNN\output\steps=2500-MAPE=0.0517.csv, 18232 , 2020-01-01
load_RNN\output\steps=2500-MAPE=0.0524.csv, 18223 , 2020-01-01
load_RNN\output\steps=2500-MAPE=0.0528.csv, 18219 , 2020-01-01
load_RNN\output\steps=2500-MAPE=0.0557.csv, 18240 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0497.csv, 18226 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0506.csv, 18223 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0507.csv, 18224 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0522.csv, 18229 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0523.csv, 18226 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0528.csv, 18240 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0531.csv, 18232 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0541, 18234 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0541.csv, 18225 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0549.csv, 18223 , 2020-01-01
load_RNN\output\steps=3000-MAPE=0.0593.csv, 18237 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0450.csv, 18221 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0499.csv, 18234 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0502.csv, 18240 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0504.csv, 18228 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0508.csv, 18231 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0509.csv, 18221 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0528.csv, 18230 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0533, 18237 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0550.csv, 18238 , 2020-01-01
load_RNN\output\steps=3500-MAPE=0.0556.csv, 18217 , 2020-01-01
load_RNN\output\steps=4000-MAPE=0.0455.csv, 18230 , 2020-01-01
load_RNN\output\steps=4000-MAPE=0.0466.csv, 18235 , 2020-01-01
load_RNN\output\steps=4000-MAPE=0.0496.csv, 18245 , 2020-01-01
load_RNN\output\steps=4000-MAPE=0.0500.csv, 18229 , 2020-01-01
load_RNN\output\steps=4000-MAPE=0.0520.csv, 18206 , 2020-01-01

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    积分：1
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