Harmful algal bloom warning based on machine learning in maritime site monitoring

作者：

Highlights：

• The coupling relationship between HABs and major environmental factors were investigated.

• The changes of algae were successfully predicted by using the few major influencing factors.

• The use of space–time clustering in combination with forecasting is recommended.

• Better prediction of HABs by combining ARIMA with deep LSTM network.

摘要

•The coupling relationship between HABs and major environmental factors were investigated.•The changes of algae were successfully predicted by using the few major influencing factors.•The use of space–time clustering in combination with forecasting is recommended.•Better prediction of HABs by combining ARIMA with deep LSTM network.

论文关键词：Harmful Algal bloom forecasting,Machine learning,Time series analysis,Ocean environment model,LSTM network

论文评审过程：Received 25 December 2020, Revised 7 March 2022, Accepted 9 March 2022, Available online 18 March 2022, Version of Record 2 April 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.108569