PredLife: Predicting Fine-Grained Future Activity Patterns-Reference-Cited by-同舟云学术

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PredLife: Predicting Fine-Grained Future Activity Patterns

Published:2023-12 Issue:6 Volume:9 Page:1658-1669
ISSN:2332-7790
Container-title:IEEE Transactions on Big Data
language:
Short-container-title:IEEE Trans. Big Data

Author:

Li Wenjing¹^ORCID,Shi Xiaodan¹^ORCID,Huang Dou¹^ORCID,Shen Xudong¹^ORCID,Chen Jinyu¹^ORCID,Kobayashi Hill Hiroki¹^ORCID,Zhang Haoran²^ORCID,Song Xuan¹^ORCID,Shibasaki Ryosuke³^ORCID

Affiliation:

1. Center for Spatial Information Science, The University of Tokyo, Kashiwa, Chiba, Japan

2. School of Urban Planning & Design, Peking University, Shenzhen, Guangdong, China

3. Interfaculty Initiative in Information Studies, University of Tokyo, Bunkyo, Tokyo, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/6687317/10314842/10235301.pdf?arnumber=10235301

Reference56 articles.

1. A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction

2. Predicting Human Mobility via Attentive Convolutional Network

3. ARIMA Models

4. Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore

5. Modifiable Areal Unit Problem on Grided Mobile Crowd Sensing: Analysis and Restoration

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