An Approach to Improve Diffusion Coefficient of Geospatial Information Model
- 10.2991/dramclr-19.2019.1How to use a DOI?
- geospatial information diffusion, diffusion coefficient, search interval, test point, background data, disaster
This paper proposes an approach to improve the diffusion coefficient of the geospatial information diffusion model. The diffusion coefficient calculated by the average distance formula is appropriately amplified to become the initial diffusion coefficient. Employing a search method, we take two test points in the search interval consisting of 0 and the initial diffusion coefficient. Comparing the errors of the two test points used in the geospatial information diffusion model, we adjust the search interval: if the error of the left test point is small, the left point of the new search interval is unchanged, and the original right point of search interval is replaced with the right test point; if the error of the right test point is small, The right point of the new interval is unchanged, and the original left point of search interval is replaced with the left test point. Repeatedly, the search interval is continuously narrowed until the distance between the two test points is less than a given value, then the search is stopped. Meanwhile, the test point with a small error will be an optimized diffusion coefficient. A case constructing a relationship between the background data and disaster, with a sample size of 30, shows that the diffusion coefficient can reduce error approximately 17%.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Chongfu Huang PY - 2019/11 DA - 2019/11 TI - An Approach to Improve Diffusion Coefficient of Geospatial Information Model BT - Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019) PB - Atlantis Press SP - 1 EP - 5 SN - 1951-6851 UR - https://doi.org/10.2991/dramclr-19.2019.1 DO - 10.2991/dramclr-19.2019.1 ID - Huang2019/11 ER -