Forschungspraxis project on traffic network reconstruction in the wake of COVID-19. This repository holds all information related to the Forschungspraxis project offered by LSR.
This report builds on the idea of the networked SEIR model to recover pandemic spread parameters and apply the identified model for simulation/prediction of pandemic activity based on COVID-19 case data, public transport schedule information and estimated mobility behavior of a population. A data-driven methodology to the problems of transient network structure recovery and time-varying strength of adjacency estimation is presented. A case study on German data is implemented and the resulting models’ performances are evaluated numerically and graphically.
Epidemic modeling, System identification, Networked control systems, Data engineering
- Supervisor: Yuhong Chen [[email protected]]
- Student: Tobias Krug [[email protected]]
- doc: overall documentation of the Forschungspraxis and related material, e.g. URL collections
- prj: software projects, documentation and related material, e.g. data sets