wqk666999 / CNN-LSTM-AttentionLinks
使用卷积神经网络-长短期记忆网络(bi-LSTM)-注意力机制对股票收盘价进行回归预测。The convolution neural network, short-term memory network and attention mechanism are used to predict the closing price.
☆279Updated last year
Alternatives and similar repositories for CNN-LSTM-Attention
Users that are interested in CNN-LSTM-Attention are comparing it to the libraries listed below
Sorting:
- CNN+LSTM+Attention predict stock☆53Updated 3 years ago
- Regression prediction of time series data using LSTM, SVM and random forest. 使用LSTM、SVM、随机森林对时间序列数据进行回归预测,注释拉满。☆190Updated 5 years ago
- Use BPNN and LSTM to forecast stock price. 使用BP神经网 络和LSTM预测股票价格,注释拉满。☆195Updated 2 years ago
- CNN+BiLSTM+Attention Multivariate Time Series Prediction implemented by Keras☆679Updated 5 years ago
- 基于pytorch搭建多特征LSTM时间序列预测☆168Updated 2 years ago
- ☆18Updated 4 years ago
- 多元多步时间序列的LSTM模型预测——基于Keras☆80Updated 3 years ago
- ☆26Updated 2 years ago
- 基于LSTM的多变量时间序列预测☆21Updated last year
- 使用随机森林、bp神经网络、LSTM神经网络、GRU对股票收盘价进行回归预测。Random forest, BP neural network, LSTM neural network and GRU are used to predict the closing pric…☆53Updated 5 years ago
- CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.☆258Updated 2 months ago
- PyTorch实现的Informer (Informer:用于长序列时间序列预测☆25Updated 2 years ago
- EEMD、LSTM、time series prediction、DO、Deep Learning☆88Updated 3 years ago
- Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction☆363Updated 3 years ago
- stock predict with MLP,CNN,RNN,LSTM,Transformer and Transformer-LSTM☆258Updated 3 years ago
- 使用LSTM、GRU、BPNN进行时间序列预测。Using LSTM\GRU\BPNN for time series forecasting. (Pytorch Edition)☆57Updated 4 years ago
- 使用ARIMA,Transformer,LSTM 对心跳时间序列数据进行预测☆17Updated last year
- Paper-Reproduce: (ESWA) Forecasting the realized volatility of stock price index: A hybrid model integrating CEEMDAN and LSTM☆65Updated last year
- 深度学习以进行时间序列预测☆665Updated 4 years ago
- used for Stock Prodiction&power prediction&Traffic prediction by ARIMA,xgboost,RNN,LSTM,TCN☆111Updated 5 years ago
- ☆250Updated last year
- ☆30Updated 2 years ago
- 使用多种算法(线性回归、随机森林、支持向量机、BP神经网络、GRU、LSTM)进行电力系统负荷预测/电力预测。通过一个简单的例子。A variety of algorithms (linear regression, random forest, support vecto…☆164Updated 4 years ago
- 基于VMD-Attention-LSTM的时间序列预测模型(代码仅使用了一个较小数据集的训练及预测,内含使用使用逻辑,适合初学者观看,模型结构是可行的,有能力的请尝试使用更大的数据集训练)☆60Updated 2 years ago
- 建立SARIMA-LSTM混合模型预测时间序列问题。以PM2.5值为例,使用UCI公开的自2013年1月17日至2015年12月31日五大城市PM2.5小时检测数据,将数据按时间段划分,使用SARIMA过滤其线性趋势,再对过滤后的残差使用LSTM进行预测,最后对预测结果进行…☆79Updated 6 years ago
- 基于统计学的时间序列预测(AR,ARM).☆274Updated 4 years ago
- transformer/self-attention for Multidimensional time series forecasting 使用transformer架构实现多维时间预测☆234Updated last year
- 使用bp神经网络预测股票价格。BP neural network is used to predict the stock price.☆37Updated 5 years ago
- 使用LSTM、ANN网络进行时间序列的多步预测。一般情况下机器学习算法在进行时间序列预测时采取一步预测的方法。该段代码将其拓展到多步预测的情形。主要改进在于数据的构建。LSTM and ANN are used to predict the time series. In …☆16Updated 4 years ago
- ☆26Updated 3 years ago