基于EEMD-TCN的数据预测模型分析
Analysis of data prediction model based on EEMD-TCN
刘会滔 1王修来2
作者信息
- 1. 南京信息工程大学人工智能学院,江苏 210044
- 2. 南京信息工程大学人工智能学院,江苏 210044;东部战区总医院医学信息数据室,江苏 210002
- 折叠
摘要
阐述一种基于集合经验模态分解(EEMD)和时间卷积网络(TCN)的组合预测模型.使用EEMD对样本数据进行分解,得到若干模态分量IMF和残差,将各个分量输入TCN模型进行预测,最后将各分量预测结果叠加获得最终结果.实验结果表明,该模型比其他对比模型具有更高的预测精度.
Abstract
This paper describes a combined prediction model based on Set Empirical Mode Decomposition(EEMD)and Time Convolutional Network(TCN).Using EEMD to decompose the sample data,obtain several modal components IMF and residuals,input each component into the TCN model for prediction,and finally superimpose the prediction results of each component to obtain the final result.The experimental results show that this model has higher prediction accuracy than other comparative models.
关键词
集合经验模态分解/时间卷积网络/数据预测模型Key words
ensemble empirical mode decomposition/time convolutional networks/data prediction models引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据