22 lines
1.2 KiB
Python
22 lines
1.2 KiB
Python
import numpy as np
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'''
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cr. ARNN - Support Information
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6.2. Wind speed dataset The wind speed dataset, which is provided by the Japan Meteorological Business Support Center,
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contains the wind speed (m/s) time series sampled every ∆𝑡 = 10 minutes between 2010 and 2012 from 𝐷 = 155 wind stations (variables) in Wakkanai, Japan9.
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As for the 155 stations, their specific locations (latitude and longitude) can be found in the original dataset file 201606241049longitudelatitude.mat accessible in https://github.com/RPcb/ARNN/tree/master/Data/wind%20speed .
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We use 𝑚 = 110 time points as the known series and make predictions on the next 𝐿 − 1 = 45 time points. As shown in Figs. 3a-3b of the main text, the performance of ARNN is better than the other methods.
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Besides, utilizing this dataset, we tested the robustness of ARNN with different prediction steps in Figs. 3c-3e of the main text, which proved the effectiveness of ARNN in any time region.
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'''
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# shape -> [155, 157819]
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data = np.loadtxt('exp/data/scale_windspeed.txt')
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print(data.shape)
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import matplotlib.pyplot as plt
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plt.figure(figsize=(12, 6))
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plt.plot(data[0,:])
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plt.title("Wind Speed Data")
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plt.xlabel("Time (dt = 10 mins)")
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plt.ylabel("Wind Speed (m/s)")
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plt.grid(True)
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plt.show() |