Applications of Robust Methods in Spatial Analysis
Spatial data analysis provides valuable information to the government as well as companies. The rapid improvement of modern technology with a geographic information system (GIS) can lead to the collection and storage of more spatial data. We developed algorithms to choose optimal locations from thos...
Saved in:
Main Author: | Selvakkadunko Selvaratnam |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-01-01
|
Series: | Journal of Probability and Statistics |
Online Access: | http://dx.doi.org/10.1155/2023/1328265 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
On Resilience Guarantees by Finite-Time Robust Control Barrier Functions With Application to Power Inverter Networks
by: Kamil Hassan, et al.
Published: (2024-01-01) -
Protocol to boost the robustness and accuracy of spatial transcriptomics algorithms using ensemble techniques
by: Jiazhang Cai, et al.
Published: (2025-03-01) -
Statistical and computational methods for enabling the clinical and translational application of spatial transcriptomics
by: Peijun Wu, et al.
Published: (2024-12-01) -
Application of Constrained Robust Independent Component Analysis in the Fault Diagnosis of Rolling Element Bearing
by: Liao Qiang, et al.
Published: (2015-01-01) -
Robustness test method for intelligent electronic device
by: Haitao JIANG, et al.
Published: (2015-12-01)