Abstract:

Big marine data possesses several typical characteristics such as large amount, multisource, multiple dimensions, multitype and so on. How to design an optimal quality inspection plan fast and control the ocean data timely becomes more and more important for the application of big marine data. Based on skyline, a method is proposed to select the optimal quality inspection plan for the quality inspection of big marine data. Firstly, the residual of acceptance quality probability of each quality inspection plans for ocean big data are calculated by Hypergeometric distribution model. Secondly, the optimal quality inspection plan is selected based on the algorithm of BlockNestedLoops (BNL), which compares the residual of acceptance quality probability of each quality inspection plans one by one. Finally, the proposed method is verified by inspecting the quality of the big marine data, which is collected by monitoring sites in a certain sea area.Key words:big marine data;quality inspection;blocknestedloops algorithm;residuals