A self organizing map (SOM) guided rule based system for freshwater tropical algal analysis and prediction

This paper describes the feasibility study of applying a hybrid combination of Kohonen self organizing feature maps (SOM) and a rule based system in predicting the biomass of selected algae division (Chlorophyta) at tropical Putrajaya Lake (Malaysia). The system was trained and tested on an over fiv...

全面介紹

Saved in:
書目詳細資料
Main Authors: Malek Abd Rashid, Sorayya Bibi Malek, Salleh, Aishah, Baba, Mohd Sapiyan, Syed Ahmad Abdul Rahman, Sharifah Mumtazah
格式: Article
語言:English
出版: Academic Journals 2011
在線閱讀:http://psasir.upm.edu.my/id/eprint/23121/1/A%20self%20organizing%20map%20%28SOM%29%20guided%20rule%20based%20system.pdf
http://psasir.upm.edu.my/id/eprint/23121/
http://www.academicjournals.org/journal/SRE/article-abstract/1179EBA40193
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Universiti Putra Malaysia
語言: English
實物特徵
總結:This paper describes the feasibility study of applying a hybrid combination of Kohonen self organizing feature maps (SOM) and a rule based system in predicting the biomass of selected algae division (Chlorophyta) at tropical Putrajaya Lake (Malaysia). The system was trained and tested on an over five years of limnological time-series data sampled from Putrajaya Lake. Results from trained SOM were used to extract rules of relationships between input variables and the Chlorophyta biomass which was used to construct a rule based system. Selected input variables were water temperature, Secchi depth and nitrate nitrogen (NO3-N). The rules extracted conformed to findings as postulated in literatures. The overall rule based system yielded an accuracy of 73%.