海洋大数据质量检测中的嵌套循环算法
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摘要
针对传统检测算法对海洋大数据质量的检测结果残差过大的问题,提出并设计了一种嵌套循环质量检测算法。利用平衡标准,确定海洋大数据质量检测参数,在此基础上,建立嵌套循环式数据质量评价集,对海洋大数据的各个指标进行检索比较,最终选择出最优的检测指标,实现海洋大数据的质量检测计算。仿真实验结果表明,嵌套循环算法能够有效降低检测残差,较传统算法的检测残差率低27.1%,具备极高的有效性。
Aiming at the problem that the residual error of the traditional detection algorithm is too large for the quality of large ocean data, a nested cyclic quality detection algorithm is proposed and designed. On this basis, nested cyclic data quality evaluation set is established to search and compare the various indicators of large ocean data. Finally, the optimal detection indicators are selected to realize the quality detection calculation of large ocean data. The simulation results show that the nested loop algorithm can effectively reduce the detection residual, which is 27.1% lower than the traditional algorithm,and has a very high efficiency.
Aiming at the problem that the residual error of the traditional detection algorithm is too large for the quality of large ocean data, a nested cyclic quality detection algorithm is proposed and designed. On this basis, nested cyclic data quality evaluation set is established to search and compare the various indicators of large ocean data. Finally, the optimal detection indicators are selected to realize the quality detection calculation of large ocean data. The simulation results show that the nested loop algorithm can effectively reduce the detection residual, which is 27.1% lower than the traditional algorithm,and has a very high efficiency.
引文
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[2]孙苗,符昱,吕憧憬,等.深度学习在海洋大数据挖掘中的应用[J].科技导报,2018,36(17):83–90.
[3]曹彤彤,曾献奎,吴吉春.嵌套抽样算法用于地下水模型评价的算例研究[J].水文地质工程地质,2017,43(2):69–76.
[4]黄冬梅,赵丹枫,魏立斐,等.大数据背景下海洋数据管理的挑战与对策[J].计算机科学,2016,43(06):17–23.