针对时序型数据的短、长期智能预测，目标跟踪以及物联网平台和系统构建
Date:
首先构建了一套长短期水质预测算法模型，首次提出了考虑相关性的深度学习预测方法；
其次建立了一套水下鱼体行为检测和预警模型；
最后构建了一套完整的水下鱼体行为检测和跟踪、水质监测和预测物联网智慧平台。
以上的工作在海南陵水新村港得到了应用示范，取得了较好的成效。
Firstly, a set of long and short-term water quality prediction algorithm model was constructed, and a deep learning prediction method considering correlation was proposed for the first time. Secondly, a set of underwater fish behavior detection and early warning model was built. Finally, a complete set of underwater fish behavior detection and tracking, water quality monitoring and prediction IoT wisdom platform was constructed. The above work has been applied and demonstrated in Xincun Port, Lingshui County, Hainan Province, China, with good results.