Article
Spatio-temporal Estimation Of Wildfire Growth 开放存取 Deposited
This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deploy ability.
- 创建者
- 证书
- 提交
- 学
- 部门
- 创建日期
- 期刊名称
- Proceedings of the ASME Dynamic Systems and Control Conference
- 语言
- 音符
This work was part of a pilot "mediated-deposit model" where library staff found potential works, later submitted for faculty review
Digital Object Identifier (DOI)
识别码: 10.1115/DSCC2013-4022
链接: https://doi.org/10.1115/DSCC2013-4022
这个DOI链接是其他人引用您工作的最佳方式。
单件
| 缩略图 | 标题 | 上传日期 | 公开度 | 行动 |
|---|---|---|---|---|
|
|
AP2013_B__1_.pdf | 2017-02-08 | 开放存取 |
|
永久链接到此页面: https://scholar.uc.edu/show/bc386t23t