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Empirical Study of Online Public Opinion Index Prediction on Real Accidents Data

机译:真实事故数据在线民意指标预测的实证研究

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摘要

With the increased online public opinion data of real accidents in the last ten years. It has been important for us to attain and analysis the online public opinion data of real accidents. In this paper, an empirical study of online public opinion index prediction over more than 30 real accidents happened in China and other places in the world has been made and experiments results has proved that the online public opinion index prediction method is useful and we got some interesting results. And we have implemented GM (1,1) model, GM (2,1) model and chaotic prediction model based prediction method in online opinion for the first time.
机译:随着近十年来实际事故在线公众舆论数据的增加。对于我们而言,获取和分析实际事故的在线民意数据非常重要。本文对中国及世界其他地区发生的30余起实际事故进行了在线舆情指标预测的实证研究,实验结果证明了在线舆情指标预测方法是有效的,并得到了一些认识。有趣的结果。并且我们首次在在线舆论中实现了基于GM(1,1)模型,GM(2,1)模型和基于混沌预测模型的预测方法。

著录项

  • 来源
    《Web-age information management》|2014年|65-76|共12页
  • 会议地点 Macau(CN)
  • 作者

    Xiao Long Deng; Yu Xiao Li;

  • 作者单位

    Key Laboratory of Trustworthy Distributed Computing and Service, Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Beijing 100876, China;

    Key Laboratory of Trustworthy Distributed Computing and Service, Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Beijing 100876, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Grey prediction; Empirical study; Real accident; Public opinion; Index prediction; Data ming;

    机译:灰色预测;实证研究;真正的偶然;舆论;指数预测;数据挖掘;
  • 入库时间 2022-08-26 14:03:40

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