Modeling of utility function for real-time prediction of spatial information

Keiichiro Sato, Ryoichi Shinkuma, Takehiro Sato, Eiji Oki, Takanori Iwai, Takeo Onishi, Takahiro Nobukiyo, Dai Kanetomo, Kozo Satoda

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Real-time prediction of spatial information has attracted a lot of attention. Machine learning enables us to provide real-time prediction of spatial information such as road traffic by using aggregated sensor data. The amount of mobile traffic is forecasted to increase exponentially, thereby causing serious transmission delays when traffic loads are heavy. If a part of the data used for predicting spatial information in real time does not arrive on time, the prediction accuracy degrades because the prediction is done without the missing data. A utility-based scheduling technique has been suggested as a way of prioritizing such delay-sensitive data. However, no study has not addressed the utility-based scheduling for the real-time prediction of spatial information. Therefore, this paper proposes a scheme that enables modeling the utility function for real- time prediction of spatial information. The scheme is roughly composed of two steps: the first creates training data from original time-series data and a machine learning model using the data, while the second models the utility function using the feature selection method in the learning model. Feature selection method enables extracting the importance of data in terms of how much the data contributes to the prediction accuracy. This paper assumes the road traffic prediction as a scenario and shows the utility function modeled by the proposed scheme using real spatial datasets. A numerical study demonstrates how the model of the utility function works effectively in prioritizing data for real-time prediction in terms of accuracy.

本文言語English
ホスト出版物のタイトル2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728109626
DOI
出版ステータスPublished - 2019 12
外部発表はい
イベント2019 IEEE Global Communications Conference, GLOBECOM 2019 - Waikoloa, United States
継続期間: 2019 12 92019 12 13

出版物シリーズ

名前2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings

Conference

Conference2019 IEEE Global Communications Conference, GLOBECOM 2019
国/地域United States
CityWaikoloa
Period19/12/919/12/13

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 情報システム
  • 信号処理
  • 情報システムおよび情報管理
  • 安全性、リスク、信頼性、品質管理
  • メディア記述
  • 健康情報学

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