Water Bloom Prediction Method Based on Holt-Winters-LSTM

Eutrophication in Taihu lake has caused extensive water blooms. Current approaches to water bloom prediction utilize only long-term memory neural networks and do not capture seasonal trend in cyanobacterial growth. To solve this problem, this paper proposed a combined algorithm based on Holt-Winters and LSTM. The accuracy and reasonableness of this algorithm were verified through experiments and analysis.