DocumentCode
2363223
Title
Prediction of red tide blooms using decision tree model
Author
Park, Sun ; Jung, Min A. ; Lee, Seong Ro ; Pyo, Se Jun ; Park, Jae Hai ; Kim, Kong Soung ; Park, Yinsoo
Author_Institution
Inst. of Inf. Sci. & Eng. Res., Mokpo Nat. Univ., Mokpo, South Korea
fYear
2011
fDate
28-30 Sept. 2011
Firstpage
710
Lastpage
713
Abstract
A red tide damages sea farming on the coast of many countries, and generally has a bad influence on the coastal environment and sea ecosystem. To enhance the prediction of red tide blooms, this paper proposes a red tide prediction method that uses decision tree. The proposed method improves the precision of prediction because the decision tree classifier is enhanced by the modeled data of the proposed preprocessing. The experimental results demonstrate that the proposed method achieves a better red tide prediction performance than other classifiers.
Keywords
aquaculture; decision trees; pattern classification; prediction theory; coastal environment; decision tree classifier; decision tree model; red tide blooms prediction; sea ecosystem; sea farming; Aquaculture; Data preprocessing; Decision trees; Predictive models; Temperature distribution; Tides; Red tide blooms; decision tree; model; prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
ICT Convergence (ICTC), 2011 International Conference on
Conference_Location
Seoul
Print_ISBN
978-1-4577-1267-8
Type
conf
DOI
10.1109/ICTC.2011.6082682
Filename
6082682
Link To Document