基于TensorFlow的时间序列预测系统  

Time Series Prediction System Based on TensorFlow Deep Learning

作　　者：刘俊利 何波[1] 胡雅萌 LIU Jun-li;HE Bo;HU Ya-meng(School of Computer Science and Technology,Southwest University of Science and Technology,Mianyang 621000)

机构地区：[1]西南科技大学计算机科学与技术学院

出　　处：《现代计算机》2019年第14期26-29,33,共5页Modern Computer

摘　　要：在日常生活中,我们常常会碰到各种各样的时间序列预测问题,如图书馆人流的预测、商品销量的预测、股价的预测,等等。TensorFlow Time Series(以下简称TFTS)是TensorFlow1.3版本中新引入的模块。TFTS专门设计一套针对时间序列预测问题的API,利用其提供的LSTM模型,可以实现在TensorFlow中快速搭建高性能时间序列预测系统。In daily life,we often encounter a variety of time series prediction problems,such as the prediction of library flow,the prediction of product sales,the prediction of stock prices and so on.The TensorFlow Time Series(hereafter referred to as TFTS)is a newly introduced module in the TensorFlow 1.3 release.TFTS has designed a set of APIs for time series prediction problems.Using its LSTM model,it can quickly build a high-performance time series prediction system in TensorFlow.

关 键 词：时间序列 TensorFlow TensorFlow TIME Series库 LSTM网络 

分 类 号：O211.61[理学—概率论与数理统计]