A Long Short-Term Memory (LSTM) neural network model is developed to provide a real-time calculation tool for monitoring the mooring line responses under the operating condition by using the vessel motion as the only input. A feature extraction method based on first order moment and second ...
full_df_scaled_array[i-time_step :i , 0:full_df_scaled_array.shape[1]]) data_x=np.array(data_x) prediction=my_model.predict(data_x) all_data.append(prediction) full_df.iloc[i,0]=prediction 对于第一个预测,有之前的 30 个值,当 for 循环第一次运行时它会检查前 30 个值并预测第 31...
plt.plot(original, color = 'red', label = 'Real Stock Price') plt.plot(pred, color = 'blue', label = 'Predicted Stock Price') plt.title('Stock Price Prediction') plt.xlabel('Time') plt.ylabel('Google Stock Price') plt.legend() plt.show() 看样子还不错,到目前为止,我们训练了模型...
单变量数据集 daily-min-temperatures importnumpyasnpimportpandasaspdfromLSTMTimeimportLSTMTimePredictor# 验证比例设置为0.1, 时间预测窗口设置为30df=pd.read_csv('./daily-min-temperatures.csv')df=df.set_index('Date')
plt.plot(original, color = 'red', label = 'Real Stock Price') plt.plot(pred, color = 'blue', label = 'Predicted Stock Price') plt.title('Stock Price Prediction') plt.xlabel('Time') plt.ylabel('Google Stock Price') plt.legend() ...
plt.plot(original,color='red',label='Real Stock Price') plt.plot(pred,color='blue',label='Predicted Stock Price') plt.title('Stock Price Prediction') plt.xlabel('Time') plt.ylabel('Google Stock Price') plt.legend() plt.show()
在不同epoch下，对2017年的数据进行预测的结果像下面的图片中所示的那样：（根据之前60天的真实数据来...
plt.plot(original, color = 'red', label = 'Real Stock Price')plt.plot(pred, color = 'blue', label = 'Predicted Stock Price')plt.title('Stock Price Prediction')plt.xlabel('Time')plt.ylabel('Google Stock Price')plt.legend()plt.show() 看样子还不错,到目前为止,我们训练了模型并用测试...
t0 = time.time() data_close = ts.get_k_data('000001',start='2019-01-01',index=True)[ 'close'].values # 取上证指数的收盘价的np.ndarray 而不是pd.Series data_close = data_close.astype('float32') # 转换数据类型 plt.plot(data_close) ...
plt.plot(original,color='red', label ='Real Stock Price') plt.plot(pred,color='blue', label ='Predicted Stock Price') plt.title('Stock Price Prediction') plt.xlabel('Time') plt.ylabel('Google Stock Price') plt.legend() plt.show() ...