Paralleled Dynamic Crowd Emotion Contagion Algorithm

Authors

Xiang Nan, 1. School of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;;
Mingmin Zhang, 2. School of Computer Science and Technology, Zhejiang University, Hangzhou 310058, China;
Lingyun Zhu, 1. School of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;;

Abstract

Abstract: As the positions of crowd usually change dynamically, then computing the contagion process becomes a challenge. There current algorithms were too time consuming to be adopted as they needed to calculate the reactions between every two objects. In order to solve this problem, a social force based contagion computing algorithm with GPU acceleration was provided. Individuals’ affection fields were projected onto two dimensional mesh grid and represented by the nine-box diary; The social force reactions between individual and nearest neighbors were computed to get the moving position; The contagion results from nearest neighbors were calculated. All of these steps were paralleled processing by GPU. Experiments show that the algorithm can efficiently increase the accuracy and speed of emotion contagion.

Recommended Citation

Nan, Xiang; Zhang, Mingmin; and Zhu, Lingyun (2020) "Paralleled Dynamic Crowd Emotion Contagion Algorithm," Journal of System Simulation: Vol. 28: Iss. 9, Article 6.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss9/6

First Page

1964

Revised Date

2016-07-11

DOI Link

https://doi.org/

Last Page

1969

CLC

TP391.9

Recommended Citation

Xiang Nan, Zhang Mingmin, Zhu Lingyun. Paralleled Dynamic Crowd Emotion Contagion Algorithm[J]. Journal of System Simulation, 2016, 28(9): 1964-1969.