Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems
A set-membership (bounded-error) estimation approach can handle small and poor quality data sets as it does not require testing of statistical assumptions which is possible only with large informative data sets. Thus, set-membership estimation can be a good tool in the modelling of agri-environmenta...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2017
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/63202/ http://psasir.upm.edu.my/id/eprint/63202/1/Set-membership%20estimation%20from%20poor%20quality%20data%20sets%20modelling%20ammonia%20volatilisation%20in%20flooded%20rice%20systems.pdf |
| _version_ | 1848854735234269184 |
|---|---|
| author | Nurulhuda, K. Struik, P. C. Keesman, K. J. |
| author_facet | Nurulhuda, K. Struik, P. C. Keesman, K. J. |
| author_sort | Nurulhuda, K. |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | A set-membership (bounded-error) estimation approach can handle small and poor quality data sets as it does not require testing of statistical assumptions which is possible only with large informative data sets. Thus, set-membership estimation can be a good tool in the modelling of agri-environmental systems, which typically suffers from limited and poor quality observational data sets. The objectives of the paper are (i) to demonstrate how six parameters in an agri-environmental model, developed to estimate NH3 volatilisation in flooded rice systems, were estimated based on two data sets using a set-membership approach, and (ii) to compare the set-membership approach with conventional non-linear least-squares methods. Results showed that the set-membership approach is efficient in retrieving feasible parameter-vectors compared with non-linear least-squares methods. The set of feasible parameter-vectors allows the formation of a dispersion matrix of which the eigenvalue decomposition reflects the parameter sensitivity in a region. |
| first_indexed | 2025-11-15T11:14:35Z |
| format | Article |
| id | upm-63202 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:14:35Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-632022018-08-20T06:30:03Z http://psasir.upm.edu.my/id/eprint/63202/ Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems Nurulhuda, K. Struik, P. C. Keesman, K. J. A set-membership (bounded-error) estimation approach can handle small and poor quality data sets as it does not require testing of statistical assumptions which is possible only with large informative data sets. Thus, set-membership estimation can be a good tool in the modelling of agri-environmental systems, which typically suffers from limited and poor quality observational data sets. The objectives of the paper are (i) to demonstrate how six parameters in an agri-environmental model, developed to estimate NH3 volatilisation in flooded rice systems, were estimated based on two data sets using a set-membership approach, and (ii) to compare the set-membership approach with conventional non-linear least-squares methods. Results showed that the set-membership approach is efficient in retrieving feasible parameter-vectors compared with non-linear least-squares methods. The set of feasible parameter-vectors allows the formation of a dispersion matrix of which the eigenvalue decomposition reflects the parameter sensitivity in a region. Elsevier 2017-02 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/63202/1/Set-membership%20estimation%20from%20poor%20quality%20data%20sets%20modelling%20ammonia%20volatilisation%20in%20flooded%20rice%20systems.pdf Nurulhuda, K. and Struik, P. C. and Keesman, K. J. (2017) Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems. Environmental Modelling & Software, 88 (2017). 138 - 150. ISSN 1364-8152 10.1016/j.envsoft.2016.11.002 |
| spellingShingle | Nurulhuda, K. Struik, P. C. Keesman, K. J. Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| title | Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| title_full | Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| title_fullStr | Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| title_full_unstemmed | Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| title_short | Set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| title_sort | set-membership estimation from poor quality data sets: modelling ammonia volatilisation in flooded rice systems |
| url | http://psasir.upm.edu.my/id/eprint/63202/ http://psasir.upm.edu.my/id/eprint/63202/ http://psasir.upm.edu.my/id/eprint/63202/1/Set-membership%20estimation%20from%20poor%20quality%20data%20sets%20modelling%20ammonia%20volatilisation%20in%20flooded%20rice%20systems.pdf |