Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system
Phytoplankton becomes a concern to the environment when it forms dense growth at the water surface, known as algal bloom. However, studies on mechanism of algal bloom are not straight forward mainly caused by uncertainty and complexity of alga ecosystems. This paper describes the analysis of limnolo...
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2023
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| author | Malek S. Salleh A. Ahmad S.M.S. |
| author2 | 35069976500 |
| author_facet | 35069976500 Malek S. Salleh A. Ahmad S.M.S. |
| author_sort | Malek S. |
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| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Phytoplankton becomes a concern to the environment when it forms dense growth at the water surface, known as algal bloom. However, studies on mechanism of algal bloom are not straight forward mainly caused by uncertainty and complexity of alga ecosystems. This paper describes the analysis of limnological time-series of Putrajaya Lake and wetlands to determine the growth of alga based on Kohonen self organizing feature maps (SOM). It specifically concentrates on the total Bacillariophyta species due to formation of largest algal composition in the Lake Putrajaya. An expert system was then developed based on the rules extracted from the SOM to model and predict the algal growth. The effectiveness of this system was tested on an actual tropical lake data which yields an acceptable high level of accuracy. � 2009 IEEE. |
| format | Conference Paper |
| id | my.uniten.dspace-29677 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| record_format | dspace |
| spelling | my.uniten.dspace-296772024-04-17T10:16:13Z Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system Malek S. Salleh A. Ahmad S.M.S. 35069976500 7003809022 24721182400 Rule based expert system Self organizing map Blooms (metal) Classifiers Expert systems Gallium alloys Information management Lakes Strength of materials Time series analysis Algal blooms Algal growth Kohonen self-organizing feature map Rule based expert system Rule based expert systems Tropical lakes Water surface Self organizing maps Phytoplankton becomes a concern to the environment when it forms dense growth at the water surface, known as algal bloom. However, studies on mechanism of algal bloom are not straight forward mainly caused by uncertainty and complexity of alga ecosystems. This paper describes the analysis of limnological time-series of Putrajaya Lake and wetlands to determine the growth of alga based on Kohonen self organizing feature maps (SOM). It specifically concentrates on the total Bacillariophyta species due to formation of largest algal composition in the Lake Putrajaya. An expert system was then developed based on the rules extracted from the SOM to model and predict the algal growth. The effectiveness of this system was tested on an actual tropical lake data which yields an acceptable high level of accuracy. � 2009 IEEE. Final 2023-12-28T07:30:45Z 2023-12-28T07:30:45Z 2009 Conference Paper 10.1109/ICIME.2009.63 2-s2.0-70349507021 https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349507021&doi=10.1109%2fICIME.2009.63&partnerID=40&md5=e14cdd2b754c8facdd1c0334a955c554 https://irepository.uniten.edu.my/handle/123456789/29677 5077085 501 504 Scopus |
| spellingShingle | Rule based expert system Self organizing map Blooms (metal) Classifiers Expert systems Gallium alloys Information management Lakes Strength of materials Time series analysis Algal blooms Algal growth Kohonen self-organizing feature map Rule based expert system Rule based expert systems Tropical lakes Water surface Self organizing maps Malek S. Salleh A. Ahmad S.M.S. Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system |
| title | Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system |
| title_full | Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system |
| title_fullStr | Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system |
| title_full_unstemmed | Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system |
| title_short | Analysis of algal growth using kohonen self organizing feature map (SOM) and its prediction using rule based expert system |
| title_sort | analysis of algal growth using kohonen self organizing feature map (som) and its prediction using rule based expert system |
| topic | Rule based expert system Self organizing map Blooms (metal) Classifiers Expert systems Gallium alloys Information management Lakes Strength of materials Time series analysis Algal blooms Algal growth Kohonen self-organizing feature map Rule based expert system Rule based expert systems Tropical lakes Water surface Self organizing maps |
| url_provider | http://dspace.uniten.edu.my/ |