Attention-based novel neural network for mixed frequency data

Xiangpeng Li; Hong Yu; Yongfang Xie; Jie Li

首页> 中文期刊> 《智能技术学报》 >Attention-based novel neural network for mixed frequency data

Attention-based novel neural network for mixed frequency data

开具论文收录证明 >>

期刊封面封底目录下载 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

It is a common fact that data(features,characteristics or variables)are collected at different sampling frequencies in some fields such as economic and industry.The existing methods usually either ignore the difference from the different sampling frequencies or hardly take notice of the inherent temporal characteristics in mixed frequency data.The authors propose an innovative dual attention-based neural network for mixed frequency data(MID-DualAtt),in order to utilize the inherent temporal characteristics and select the input characteristics reasonably without losing information.According to the authors’knowledge,this is the first study to use the attention mechanism to process mixed fre-quency data.The MID-DualAtt model uses the frequency alignment method to trans-form the high--frequency variables into observation vectors at low frequency,and more critical input characteristics are selected for the current prediction index by attention mechanism.The temporal characteristics are explored by the encoder-decoder with attention based on long-short-term memory networks(LSTM).The proposed MID-DualAtt has been tested in practical application,and the experimental results show that it has better prediction ability than the compared models.

著录项

来源
《智能技术学报》 |2021年第3期|P.301-311|共11页
作者
Xiangpeng Li; Hong Yu; Yongfang Xie; Jie Li;
展开▼
作者单位

Chongqing key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing China;

Chongqing key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing China;

School of Information Science and Engineering Central South University Changsha China;

School of Metallurgy and Environment Central South University Changsha China;

展开▼
原文格式 PDF
正文语种 chi
中图分类 TN9;
关键词
network; decoder; mixed;

相似文献

中文文献
外文文献
专利

Attention-based novel neural network for mixed frequency data

摘要

著录项

相似文献

相关主题

期刊订阅