文献知网节
  • 记笔记
摘要:In order to solve the accuracy problem of the prediction algorithm for the lowest airfare in the future,this paper presents an United Intelligent Forecasting algorithm(UIF) consisting of two sub-algorithms,the Composite Weighted Time Series method(CWTS) and the Similarity Time Average method(STA) based on the idea of time series.CWTS calculates the sub-price on the target day from the quoted prices on the same day and a period of time in the past.STA calculates the sub-price on the target day from the prices on the similar period of time.Experiments on the real datasets show that UIF outperforms the traditional prediction algorithm and provides enhanced accuracy for airfare prediction.This airfare forecasting model based on time series can effectively solve the predictive conflict between sequences with smooth and fluctuating trends and thus a class of predictive analysis problems for the lowest airfare of air tickets at all kinds of time points are solved.
会议名称:

CENet 2017-the 7th International Conference on Computer Engineering and Networks

会议时间:

2017-07-22

会议地点:

中国上海

  • 专辑:

    基础科学

  • 专题:

    数学

  • 分类号:

    O211.61

  • 手机阅读
    即刻使用手机阅读
    第一步

    扫描二维码下载

    "移动知网-全球学术快报"客户端

    第二步

    打开“全球学术快报”

    点击首页左上角的扫描图标

    第三步

    扫描二维码

    手机同步阅读本篇文献

  • CAJ下载
  • PDF下载

下载手机APP用APP扫此码同步阅读该篇文章

下载:3 页码:417-423 页数:7 大小:267k

相关推荐
  • 相似文献
  • 读者推荐
  • 相关基金文献
  • 关联作者
  • 相关视频