Abstract: We use a time-series mining algorithm to fuse the dynamic sea surface temperature (SST) data in order to predict the future values and the trend. An improved method is proposed that uses the parabola regression model to forecast the future SST values based on median smooth and a threshold limit. By modification to the judgment of inflection points, the parabola regression model is improved in the trend prediction. Experiments show that the improved method has a better effect on the forecast of the slowly varying dynamic SST data.

Key words: mining, sea surface temperature, time fusion, time-series