An Induction Scheme of Fast Initiative-Evacuation Based on Social Graphs

다국어 초록 (Multilingual Abstract)

Early evacuations reduce the damage caused by catastrophic events such as terrorism, tsunamis, heavy rains,landslides, and river floods. However, even when warnings are issued, people do not easily evacuate duringthese events. To shorten the evacuation time, initiative-evacuation and its executors, initiative evacuees, arecrucial in inducing other evacuations. The initiative evacuees take the initiative in evacuating and call out totheir surroundings. This paper proposes a fast method to induce initiative-evacuation based on social graphs.
The candidates are determined in descending order of the number of links for each person. The proposed methodwas evaluated through simulations. The simulation results showed a significant reduction in evacuation time.

참고문헌 (Reference)

1 Kozo Keikaku Engineering Inc, "artisoc Cloud"

2 Y. Yang, "Write skew and Zipf distribution : evidence and implications" 12 (12): 21-, 2016

3 Alexandros Rigos, "The cry wolf effect in evacuation: A game-theoretic approach" Elsevier BV 526 : 120890-, 2019

4 Nicholas A. Christakis, "Social Network Sensors for Early Detection of Contagious Outbreaks" Public Library of Science (PLoS) 5 (5): e12948-, 2010

5 Jesús M. Almendros-Jiménez, "Retrieval of Social Network Data for Points of Interest in OpenStreetMap" KIPS-CSWRG 11 (11): 1-1, 2021

6 Peng Mei, "Research on Emotion Simulation Method of Large-scale Crowd Evacuation Under Particle Model" KIPS-CSWRG 1 (1): 1-20, 2021

7 M. Drobyshevskiy, "Random graph modeling : a survey of the concepts" 52 (52): 1-36, 2019

8 Huashan Cao, "Personalized Web Service Recommendation Method Based on Hybrid Social Network and Multi-Objective Immune Optimization" 한국정보처리학회 17 (17): 426-439, 2021

9 Liqiang Sun, "POI Recommendation Method Based on Multi-Source Information Fusion Using Deep Learning in Location-Based Social Networks" 한국정보처리학회 17 (17): 352-368, 2021

10 Chris J. Kuhlman, "Natural disaster evacuation modeling: the dichotomy of fear of crime and social influence" Springer Science and Business Media LLC 12 (12): 2021

11 Jun Li ; Haoxiang Zhang ; Zhongrui Ni, "Improved Social Force Model based on Navigation Points for Crowd Emergent Evacuation" 한국정보처리학회 16 (16): 1309-1323, 2020

12 H. Shao, "Forecasting the flu: designing social network sensors for epidemics"

13 C. D. Wickens, "False alerts in air traffic control conflict alerting system : Is there a"cry wolf"effect?" 51 (51): 446-462, 2009

14 Junji Urata, "Dynamics of local interactions and evacuation behaviors in a social network" Elsevier BV 125 : 103056-, 2021

15 S. Tsugawa, "Dynamic social network analysis with heterogeneous sensors in ambient environment" 3 : 9-18, 2014

16 K. Uchida, "A model evaluating effect of disaster warning issuance conditions on"cry wolf syndrome"in the case of a landslide" 218 (218): 530-537, 2012

17 T. Ichinose, "A fast induction method of initiative-evacuation based on social graphs" 2022