Short-term prediction of marine sensor data with fuzzy clustering

In predicting water quality variables in the short term, a novel technique using fuzzy pattern similarity-based fuzzy clustering has been proposed. The experimental results show that the proposed method outperforms than existing similar methods for sea water temperature and conductivity data sets from a marine sensor network for environmental monitoring. The short-term prediction of water quality variables has immense benefit in aquaculture and fisheries industries for decision-making purposes.