基于LSTM神经网络的海量边缘计算数据处理方法
Processing Method of Massive Edge Computing Data Based on LSTM Neural Network
姚文广 1陈思宁1
作者信息
- 1. 傲拓科技股份有限公司,江苏 南京 210012
- 折叠
摘要
传统海量边缘计算数据处理方法直接对海量边缘计算数据实施压缩,未对海量边缘计算数据进行动态合并处理,处理效果差.因此,该文提出基于LSTM神经网络的海量边缘计算数据处理方法,该方法对海量边缘计算数据进行动态合并处理,为决策和应用提供更全面和准确的信息支持;对合并的数据进行压缩,提高处理效率;最后基于LSTM神经网络,实现海量边缘计算数据的处理,实验结果表明该研究方法处理效果更好.
Abstract
The traditional massive edge computing data processing method directly compresses the massive edge computing data,but does not dynamically merge the massive edge computing data,so the processing effect is poor.Therefore,this paper proposes a massive edge computing data processing method based on LSTM neural network.This method dynamically merges massive edge computing data to provide more comprehensive and accurate information support for decision-making and application;Compress the merged data to improve processing efficiency;Finally,based on LSTM neural network,massive edge computing data are processed,and the experimental results show that the processing effect of this research method is better.
关键词
LSTM神经网络/海量边缘计算数据/海量数据/处理方法Key words
LSTM neural network/massive edge computing data/massive data/processing method引用本文复制引用
出版年
2024
NETL
NSTL
万方数据