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Intelligent System for Human Behavior Analysis and Reasoning Following Large-Scale Disasters

Authors:

Ryosuke ShibasakiAuthors Info & Claims

IEEE Intelligent Systems, Volume 28, Issue 4

Pages 35 - 42

https://doi.org/10.1109/MIS.2013.35

Published: 01 July 2013 Publication History

Abstract

By mining "big GPS records" of 1.6 million users, an intelligent system automatically discovers, analyzes, and simulates population evacuations during the Great East Japan Earthquake and the Fukushima Daiichi nuclear accident.

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Thakur DPal A(2023)Subsampled Randomized Hadamard Transformation-based Ensemble Extreme Learning Machine for Human Activity RecognitionACM Transactions on Computing for Healthcare10.1145/36348135:1(1-23)Online publication date: 27-Nov-2023
https://dl.acm.org/doi/10.1145/3634813
Lu DZhang GJia X(2023)Stochastic Optimal Intervention for Robot-Assisted Crowd EvacuationIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.332542425:5(3812-3827)Online publication date: 27-Oct-2023
https://dl.acm.org/doi/10.1109/TITS.2023.3325424
Yabe TTsubouchi KShimizu TSekimoto YUkkusuri STeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search BehaviorProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330697(2707-2717)Online publication date: 25-Jul-2019
https://dl.acm.org/doi/10.1145/3292500.3330697
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Published In

IEEE Intelligent Systems Volume 28, Issue 4

July 2013

111 pages

ISSN:1541-1672

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Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 July 2013

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Thakur DPal A(2023)Subsampled Randomized Hadamard Transformation-based Ensemble Extreme Learning Machine for Human Activity RecognitionACM Transactions on Computing for Healthcare10.1145/36348135:1(1-23)Online publication date: 27-Nov-2023
https://dl.acm.org/doi/10.1145/3634813
Lu DZhang GJia X(2023)Stochastic Optimal Intervention for Robot-Assisted Crowd EvacuationIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.332542425:5(3812-3827)Online publication date: 27-Oct-2023
https://dl.acm.org/doi/10.1109/TITS.2023.3325424
Yabe TTsubouchi KShimizu TSekimoto YUkkusuri STeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search BehaviorProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330697(2707-2717)Online publication date: 25-Jul-2019
https://dl.acm.org/doi/10.1145/3292500.3330697
Bi CFu BChen JZhao YYang LDuan YShi Y(2019)Machine learning based fast multi-layer liquefaction disaster assessmentWorld Wide Web10.1007/s11280-018-0632-822:5(1935-1950)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s11280-018-0632-8
Wen XLin YPelechrinis K(2018)Event Analytics via Discriminant Tensor FactorizationACM Transactions on Knowledge Discovery from Data10.1145/318445512:6(1-38)Online publication date: 10-Oct-2018
https://dl.acm.org/doi/10.1145/3184455
Li TXie NZeng CZhou WZheng LJiang YYang YHa HXue WHuang YChen SNavlakha JIyengar S(2017)Data-Driven Techniques in Disaster Information ManagementACM Computing Surveys10.1145/301767850:1(1-45)Online publication date: 10-Mar-2017
https://dl.acm.org/doi/10.1145/3017678
Wen XLin YPelechrinis KMukhopadhyay SZhai CBertino ECrestani FMostafa JTang JSi LZhou XChang YLi YSondhi P(2016)PairFacProceedings of the 25th ACM International on Conference on Information and Knowledge Management10.1145/2983323.2983837(519-528)Online publication date: 24-Oct-2016
https://dl.acm.org/doi/10.1145/2983323.2983837
Song XZhang QSekimoto YShibasaki RYuan NXie X(2016)Prediction and Simulation of Human Mobility Following Natural DisastersACM Transactions on Intelligent Systems and Technology10.1145/29708198:2(1-23)Online publication date: 2-Nov-2016
https://dl.acm.org/doi/10.1145/2970819
Wang YXie ZXu KDou YLei Y(2016)An efficient and effective convolutional auto-encoder extreme learning machine network for 3d feature learningNeurocomputing10.1016/j.neucom.2015.10.035174:PB(988-998)Online publication date: 22-Jan-2016
https://dl.acm.org/doi/10.1016/j.neucom.2015.10.035
Wang YDou YLiu XLei Y(2016)PR-ELMNeurocomputing10.1016/j.neucom.2015.08.066173:P3(1073-1081)Online publication date: 15-Jan-2016
https://dl.acm.org/doi/10.1016/j.neucom.2015.08.066
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Large-Scale Auto-GPS Analysis for Discerning Behavior Change during Crisis

Prediction of human emergency behavior and their mobility following large-scale disaster

Modeling and probabilistic reasoning of population evacuation during large-scale disaster

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