Skip to main navigation
Skip to search
Skip to main content
Hong Kong Baptist University Home
Help & FAQ
Link opens in a new tab
Search content at Hong Kong Baptist University
Home
Scholars
Departments / Units
Research Output
Projects / Grants
Prizes / Awards
Activities
Student theses
Datasets
Sparse matrix computation for air quality forecast data assimilation
Michael K. Ng
, Zhaochen Zhu
*
*
Corresponding author for this work
Department of Mathematics
Research output
:
Contribution to journal
›
Journal article
›
peer-review
4
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Sparse matrix computation for air quality forecast data assimilation'. Together they form a unique fingerprint.
Sort by:
Weight
Alphabetically
Keyphrases
Data Assimilation
100%
Air Quality Prediction
100%
Forecast Data
100%
Sparse Matrix Computation
100%
Chemical Species
75%
Ensemble Kalman Filter (EnKF)
75%
Multiple Chemicals
25%
PM10
25%
Numerical Examples
25%
Computational Methods
25%
Particulate Matter 2.5 (PM2.5)
25%
Matrix Structure
25%
Observational Data
25%
NO 2
25%
Air Quality Data
25%
SO 2
25%
Kalman Filter Algorithm
25%
Combined Observation
25%
Forecasting System
25%
Sparse Observation
25%
Real Air
25%
Update Equation
25%
Mathematics
Kalman Filtering
100%
Sparse Matrix
100%
Matrix Computation
100%
Matrix (Mathematics)
33%
Numerical Example
33%
Observation Data
33%
Filter Method
33%
Earth and Planetary Sciences
Data Assimilation
100%
Air Quality
100%
Kalman Filter
60%
Particular Matter 2.5
20%
Physics
Data Assimilation
100%