Dong, G.-Z. and Chen, D.-Y., 2019. Quality control algorithm for marine meteorological data based on interest degree association rules. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 173–176. Coconut Creek (Florida), ISSN 0749-0208.
In order to improve the quality of ocean drifting buoy observation data, a new association rule mining algorithm based on interest degree model is proposed. The association rule algorithm is used to mine the buoy observation data, and all related pairs are extracted to form a sample library. Through two sets of data experiments, when the correlation coefficient t is constant, the larger the parameter u is, the fewer the records are excavated. And at the same time, the less the abnormal records are mined, the smaller the detection rate will be. Although there has been progress, there has been no significant improvement. The signs are still far away from achieving the goal of sharing. This paper put forward a new quality control algorithm for marine meteorological data based on interest degree association rules.