Name
Abstract | ||
|---|---|---|
Dynamic data driven simulation dynamically assimilates observation data at runtime to improve the simulation results. Typically, the observations are \"hard data\" that are data collected from sensors. In this paper we consider dynamic data driven simulation with soft data, which are data coming from human reports. Compared with the quantified hard data, soft data are qualitative, fuzzy and subject to human judgment. This paper proposes a method to convert soft data information to quantified data based on fuzzy set theory, and then combines soft and hard data to carry out data assimilation. We apply this method to dynamic data driven simulation of wildfire spread and show that the accuracy of simulation is significantly improved by assimilating both hard and soft data. |
Year | Venue | Keywords |
|---|---|---|
2014 | SpringSim (TMS-DEVS) | design,experimentation,data assimilation,soft data,particle filter,wildfire simulation,measurement,simulation support systems,dynamic data driven simulation,types of simulation,simulation theory,performance |
DocType | Citations | PageRank |
Conference | 2 | 0.49 |
References | Authors | |
12 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Long | 1 | 4 | 1.89 |
| Xiaolin Hu | 2 | 33 | 4.72 |