과제정보
This work was partially supported by JSPS KAKENHI (Grant No. JP22K12009), Hokuriku Regional Management Service Association, and Hoso Bunka Foundation.
참고문헌
- C. D. Wickens, S. Rice, D. Keller, S. Hutchins, J. Hughes, and K. Clayton, "False alerts in air traffic control conflict alerting system: Is there a "cry wolf" effect?," Human Factors, vol. 51, no. 4, pp. 446-462, 2009. https://doi.org/10.1177/0018720809344720
- K. Uchida, "A model evaluating effect of disaster warning issuance conditions on "cry wolf syndrome" in the case of a landslide," European Journal of Operational Research, vol. 218, no. 2, pp. 530-537, 2012. https://doi.org/10.1016/j.ejor.2011.10.050
- A. Rigos, E. Mohlin, and E. Ronchi, "The cry wolf effect in evacuation: a game-theoretic approach," Physica A: Statistical Mechanics and its Applications, vol. 526, article no. 120890, 2019. https://doi.org/10.1016/j.physa.2019.04.126
- J. Urata and E. Hato, "Dynamics of local interactions and evacuation behaviors in a social network," Transportation Research Part C: Emerging Technologies, vol. 125, article no. 103056, 2021. https://doi.org/10.1016/j.trc.2021.103056
- C. J. Kuhlman, A. Marathe, A. Vullikanti, N. Halim, and P. Mozumder, "Natural disaster evacuation modeling: the dichotomy of fear of crime and social influence," Social Network Analysis and Mining, vol. 12, article no. 13, 2022. https://doi.org/10.1007/s13278-021-00839-8
- M. Drobyshevskiy and D. Turdakov, "Random graph modeling: a survey of the concepts," ACM Computing Surveys, vol. 52, no. 6, pp. 1-36, 2019.
- T. Ichinose and T. Kawakami, "A fast induction method of initiative-evacuation based on social graphs," in Proceedings of the World IT Congress 2022, Jeju, Korea, 2022.
- J. M. Almendros-Jimenez, A. Becerra-Teron, and M. Torres, "The retrieval of social network data for Pointsof-Interest in Open-StreetMap," Human-centric Computing and Information Sciences, vol. 11, article no. 10, 2021. https://doi.org/10.22967/HCIS.2021.11.010
- H. Cao, "Personalized web service recommendation method based on hybrid social network and multiobjective immune optimization," Journal of Information Processing Systems, vol. 17, no. 2, pp. 426-439, 2021. https://doi.org/10.3745/JIPS.01.0071
- L. Sun, "POI recommendation method based on multi-source information fusion using deep learning in location-based social networks," Journal of Information Processing Systems, vol. 17, no. 2, pp. 352-368, 2021. https://doi.org/10.3745/JIPS.01.0068
- N. A. Christakis and J. H. Fowler, "Social network sensors for early detection of contagious outbreaks," PLoS One, vol. 5, no. 9, article no. e12948, 2010. https://doi.org/10.1371/journal.pone.0012948
- S. Tsugawa, H. Ohsaki, Y. Itoh, N. Ono, K. Kagawa, and K. Takashima, "Dynamic social network analysis with heterogeneous sensors in ambient environment," Social Networking, vol. 3, pp. 9-18, 2014. https://doi.org/10.4236/sn.2014.31002
- H. Shao, K. S. M. Hossain, H. Wu, M. Khan, A. Vullikanti, B. A. Prakash, M. Marathe, and N. Ramakrishnan, "Forecasting the flu: designing social network sensors for epidemics," 2016 [Online]. Available: https://arxiv.org/abs/1602.06866.
- P. Mei, G. Ding, Q. Jin, and F. Zhang, "Research on emotion simulation method of large-scale crowd evacuation under particle model," Human-centric Computing and Information Sciences, vol. 11, article no. 1, 2021. https://doi.org/10.22967/HCIS.2021.11.001
- J. Li, H. Zhang, and Z. Ni, "Improved social force model based on navigation points for crowd emergent evacuation," Journal of Information Processing Systems, vol. 16, no. 6, pp. 1309-1323, 2020. https://doi.org/10.3745/JIPS.04.0199
- Kozo Keikaku Engineering Inc., "artisoc Cloud," 2021 [Online]. Available: https://mas.kke.co.jp/en/.
- Y. Yang and J. Zhu, "Write skew and Zipf distribution: evidence and implications," ACM Transactions on Storage, vol. 12, no. 4, article no. 21, 2016.