用python写一段lstm时间序列模型的代码

import numpy as np
from keras.models import Sequential
from keras.layers import LSTM, Dense

# 随机生成时间序列数据
data = np.random.rand(100, 10, 1)

# 创建LSTM模型
model = Sequential()
model.add(LSTM(64, input_shape=(10, 1)))
model.add(Dense(1))

# 编译模型
model.compile(loss='mse', optimizer='adam')

# 训练模型
model.fit(data, np.random.rand(100, 1), epochs=10, batch_size=16)

# 预测新数据
X = np.random.rand(1, 10, 1)
y_pred = model.predict(X)

print(y_pred)