对应的中文名字:时间戳("Time stamp");系统发电功率;风速;风向;气压;空气温度。 数据开始位置 编辑 数据截止位置 编辑 3.项目文件夹 编辑 data文件装载风力发电数据集 CEEMDAN-LSTM-CNN-CBAM.py是CEEMDAN-LSTM-CNN-CBAM模型 version.py是查看自己本地目前库的版本 imf.png保存的是分解的IMF r...
为了更好地对股票价格进行预测,进而为股民提供合理化的建议,提出了一种在结合长短期记忆网络(LSTM)和卷积神经网络(CNN)的基础上引入注意力机制的股票预测混合模型(LSTM-CNN-CBAM),该模型采用的是端到端的网络结构,使用LSTM来提取数据中的时序特征,利用CNN挖掘数据中的深层特征,通过在网络结构中加入注意力机制——...
针对旋转机械故障特征不明显,故障识别准确率低的问题,提出了一种能够提取故障信号特征并且能够准确识别的LSTM-CNN-CBAM智能诊断模型.首先,使用小波包变换对旋转机械原始振动信号进行特征提取,得到具有时频特性的能量谱序列,将其归一化后作为数据集来训练模型;其次,通过LSTM提取数据的时间特性,利用卷积神经网络CNN和注意力...
This study introduces an innovative deep learning model, CNN-CBAM-LSTM, which integrates the convolutional block attention module (CBAM) to enhance the extraction of both long- and short-term features. The model's performance is assessed using the Australian Standard & Poor's 200 Index (AS51),...
The multi-head attention mechanism and CBAM capture the time correlation in the stock time series, whereas the CNN integrates the characteristics of stock data. CNN-CBAM-LSTM addresses the issue of feature extraction existing in traditional machine learning. There is no manual extraction from the ...
used as input to the convolutional neural network for feature extraction; Then, the weights of channel features and spatial features are assigned to the extracted features by CBAM, and the weighted features are then input into the Long Short-Term Memory (LSTM) network to learn temporal features....