Red tide is a temporary natural phenomenon involving harmful algal blooms (HABs) in
company with a changing sea color from normal to red or reddish brown, and which has a
bad influence on coast environments and sea ecosystems. Recent wide spread and persistent
HABs give seriously impact public health and the economy of fisheries along coasts of many
countries, since it mainly kills fish mainly and results in occasional shellfish poisoning. If we
can predict the occurrence of red tide, we will be able to minimize the damage of HABs by a
quick preparation of mitigation activity. To enhance the automatic forecast of red tide, this
paper proposes a red tide prediction method that uses ensemble method. The proposed
method can improves the precision of forecast results since the ensemble classifier is
enhanced by optimal data of the proposed preprocessing.