Prediction of red tide blooms using decision tree model

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.