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

作　　者：姚文广 陈思宁 YAO Wenguang;CHEN Sining(Aotuo Technology Co.,Ltd.,Nanjing 210012,China)

机构地区：[1]傲拓科技股份有限公司,江苏南京210012

出　　处：《数字通信世界》2024年第7期70-72,共3页Digital Communication World

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。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 

分 类 号：G642[文化科学—高等教育学] TP3[文化科学—教育学]