基于LSTM的网络流量预测研究

Research on Network Traffic Prediction Based on LSTM

伴随着我国社会的不断进步和发展,网络已经在我们生活中扮演着至关重要的角色,慢慢地我们已经进入了网络大数据的时代。使用网络流量数据预测今后短期及长期的流量趋势,对企业和商家制定营销战略和优化发展布局有着至关重要的作用。对于怎样利用这些网络流量数据来分析和预测以后的流量趋势这一问题受到各界研究者的广泛关注。研究应用到长短期记忆(LSTM)模型对收集到的某网站日活流量进行更深层次的发掘和预测。

With the continuous progress and development of our society,the internet has played a crucial role in our daily lives,and gradually we have entered the era of online big data.Using network traffic data to predict future short-term and long-term traffic trends is crucial for enterprises and businesses to formulate marketing strategies and optimize their development layout.How to use these network traffic data to analyze and predict future traffic trends has attracted widespread attention from researchers from all walks of life.The long-term and short-term memory(LSTM)model is applied in this research to further explore and predict the daily live traffic of a website collected.