Dynamic parameter calibration framework for opinion dynamics models

HIGHLIGHTS

  • who: Jiefan Zhu and collaborators from the College of Systems Engineering, National University of Defense Technology, Changsha, China have published the paper: Dynamic Parameter Calibration Framework for Opinion Dynamics Models, in the Journal: Entropy 2022, 24, 1112. of /2022/
  • what: To solve this problem the authors propose a dynamic framework that combines a genetic algorithm and a pArticle filter algorithm to dynamically calibrate the parameters of the opinion dynamics model. The authors design a fitness function in accordance with public opinion and search for a set of model parameters that best match the initial observation . . .

     

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