Jieling Wu

dblp:167/7742 · DBLP profile ↗
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2ranked-venue papers in the field
2as first author
2since 2021 · last 2022
—ORCID · conflict

Domains — venue-derived; a paper can count in several

Big Data, Cloud & Distributed Data Systems · 2 (2 first)
YearPublicationVenuePosition
2022 Study on Statistical Analysis of Post-Earthquake Road Use Recovery and Its Application
abstract
Efficient road recovery is essential for people’s wellbeing and economic recovery. The three prefectures on the Pacific side of the Tohoku region (Fukushima, Miyagi, and Iwate), are relatively similar to the three prefectures (Shizuoka, Aichi, and Mie) in the Tokai region in terms of the topographical environment. The purpose of this study is to simulate the recovery of local roads in the Tokai region after the Nankai Trough earthquake, which is expected to occur in the near future based on data from the 2011 Tohoku Earthquake. We identified regional characteristics and other factors influencing road recovery from previous cluster analysis and GIS visualization of driving data from the Tohoku region in the six months following the 2011 earthquake. However, we found that the cluster parameters were too broad, so in this study, we re-clustered the coastal and inland areas and applied stepwise discriminant analysis to construct a road recovery prediction model that can help guide the recovery of municipal roads in the Tokai region after the expected Nankai Trough earthquake.
Jieling Wu, Mitsugu Saito
IEEE Big Data1
2021 Big Data Analysis for Predicting Post-Earthquake Municipal Road Recovery
abstract
Post-disaster road recovery is important.
Jieling Wu, Mitsugu Saito
IEEE BigData1