搜索资源列表
LSTM
- 用于运行LSTM的预测代码，例子是国际航班客流量。使用语言为python.(The forecast code used to run LSTM is an example of international flight traffic. The language used is python.)
time
- 时序预测，预测下一个月乘客数量。采用lstm神经网络来预测(Time series prediction)
lstm
- 使用lstm神经网络预测时间序列，同时对参数选择进行优化(Time series prediction using LSTM neural network, the selection of the parameters are optimized)
LSTM_main
- LSTM（Long Short-Term Memory）是长短期记忆网络，是一种时间递归神经网络，适合于处理和预测时间序列中间隔和延迟相对较长的重要事件。(LSTM (Long Short-Term Memory) is a long and short term memory network. It is a kind of time recurrent neural network, which is suitable for dealing with and predicting impo
lstm
- 循环神经网络LSTM可以预测时间序列数据，根据历史时刻的信息预测未来时刻的信息(the recurrent neural network is very useful to predict data in the future)
LSTM-单变量多步
- 用jupyter notebook 实现深度学习LSTM单变量多步的时间序列预测(Using jupyter notebook to realize multi-step time series prediction of deep learning LSTM)
LSTM预测
- 可以用于LSTM预测，数据，和权重更新程序已上传(Can be used for LSTM prediction)
LSTM
- lstm时间预测matlab代码。程序说明：DATA.mat 是一行时序值， numdely 是用前numdely个点预测当前点，cell_num是隐含层的数目，cost_gate 是误差的阈值。直接在命令行输入RunLstm(numdely,cell_num,cost_gate)即可(This is the matlab code of LSTM time prediction. Program descr iption: data.mat is a row of sequential va
emd-lstm
- 基于经验模态分解成多个模态和一个残余量，再利用长短神经网络预测分别训练每一个模态和残余量，最后重构结果，得到预测结果(Prediction based on empirical mode decomposition and long short neural network)
TCN-with-attention-master
- 基于注意力的的方法，预测使用的tcn，tcn是比lstm更好的一种预测方法，附数据(Based on the attention method, TCN is better than LSTM in prediction, with data attached)
stock_predict_with_LSTM-master
- 基于python的LSTM做股票预测源代码(Based on Python LSTM stock forecast source code)
股票市场预测
- LSTM 作为预测模型，使用贝叶斯优化算法来实现股票预测的功能(LSTM as a prediction model, uses Bayesian optimization algorithm to achieve the function of stock forecasting)
LSTM
- 金融数据使用案例 在Matlab 中把文件夹加入工作路径，在命令行中输入 RunLstm(numdely,cell_num，cost_gate)即可。其中： numdely 是选择预测点的数目 cell_num 是隐含层的结点数目 cost_gate是误差的阈值（此处一般取0.25）(Financial data use cases Add the folder to the working path in Matlab, and enter RunLstm(numdely,cell_nu
hybrid-ARIMA-LSTM-model-master
- 使用LSTM-ARIMA模型进行混合预测，ARIMA做线性部分的预测，LSTM做非线性部分(LSTM-ARIMA model is used for mixed prediction, ARIMA for linear prediction and LSTM for nonlinear prediction)