Shahrood University of Technology Journal of AI and Data Mining 2322-5211 7 3 2019 07 01 A Data-driven Method for Crowd Simulation using a Holonification Model 403 409 1314 10.22044/jadm.2018.6854.1808 EN J. Peymanfard School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. N. Mozayani School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran. Journal Article 2018 03 13 In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it is. For this reason, we use simple rules for holonification. Using real-world data, we model the rules for joining each agent to a holon and leaving it with random forests. Then we use this model in simulation. Also, because we use data from a specific environment, we test the model in another environment. The result shows that the rules derived from the first environment exist in the second one. It confirms the generalization capabilities of the proposed method. https://jad.shahroodut.ac.ir/article_1314_c7e57d1c7ccef9aceb8a26e12e643ea8.pdf