How to Predict Seawater Temperature for Sustainable Marine Aquaculture (Student Abstract)

2020-06-02

Proceedings of the AAAI Conference on Artificial Intelligence, 34

Volume

Vol. 34 No. 10: Issue 10: AAAI-20 Student Tracks

Student Abstract Track

The increasing global demand for marine products has turned attention to marine aquaculture. In marine aquaculture, appropriate environment control is important for a stable supply. The influence of seawater temperature on this environment is significant and accurate prediction is therefore required. In this paper, we propose and describe the implementation of a seawater prediction method using data acquired from real aquaculture areas and neural networks. Our evaluation experiment showed that hourly next-day prediction has an average error of about 0.2 to 0.4 ◦C and daily prediction of up to one week has an average error of about 0.2 to 0.5 ◦C. This is enough to meet actual worker need, which is within 1 ◦C error, thus confirming that our seawater prediction method is suitable for actual sites.

10.1609/aaai.v34i10.7216