Forecasting biotoxin contamination in mussels across production areas of the Portuguese coast with Artificial Neural Networks
作者：
Highlights：
• Shellfish contamination poses severe constraints to shellfisheries.
• Prediction of mussel contamination by diarrhetic shellfish poisoning (DSP) toxins.
• Better predictions for short-term forecasting horizons for all models evaluated.
• Using oceanographic, atmospheric and biological time-series variables.
• Accurate one-week predictions based on DSP and toxic phytoplankton cell variables.
摘要
•Shellfish contamination poses severe constraints to shellfisheries.•Prediction of mussel contamination by diarrhetic shellfish poisoning (DSP) toxins.•Better predictions for short-term forecasting horizons for all models evaluated.•Using oceanographic, atmospheric and biological time-series variables.•Accurate one-week predictions based on DSP and toxic phytoplankton cell variables.
论文关键词：Time series,Forecasting,Artificial Neural Networks,Biotoxins,Shellfish contamination,Harmful algal blooms
论文评审过程：Received 13 April 2022, Revised 10 September 2022, Accepted 12 September 2022, Available online 17 September 2022, Version of Record 1 October 2022.
论文官网地址：https://doi.org/10.1016/j.knosys.2022.109895
