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Modeling and Analysis in Marine Big Data: Advances and Challenges

机译：海洋大数据建模与分析：进步与挑战

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摘要

It is aware that big data has gathered tremendous attentions from academic research institutes, governments, and enterprises in all aspects of information sciences. With the development of diversity of marine data acquisition techniques, marine data grow exponentially in last decade, which forms marine big data. As an innovation, marine big data is a double-edged sword. On the one hand, there are many potential and highly useful values hidden in the huge volume of marine data, which is widely used in marine-related fields, such as tsunami and red-tide warning, prevention, and forecasting, disaster inversion, and visualization modeling after disasters. There is no doubt that the future competitions in marine sciences and technologies will surely converge into the marine data explorations. On the other hand, marine big data also brings about many new challenges in data management, such as the difficulties in data capture, storage, analysis, and applications, as well as data quality control and data security. To highlight theoretical methodologies and practical applications of marine big data, this paper illustrates a broad view about marine big data and its management, makes a survey on key methods and models, introduces an engineering instance that demonstrates the management architecture, and discusses the existing challenges.
机译：众所周知，大数据已经在信息科学的各个方面引起了学术研究机构，政府和企业的极大关注。随着海洋数据采集技术多样性的发展，近十年来海洋数据呈指数增长，形成了海洋大数据。作为一项创新，海洋大数据是一把双刃剑。一方面，海量海量数据中隐藏着许多潜在的，非常有用的价值，这些数据已广泛用于与海有关的领域，例如海啸和赤潮预警，预防和预报，灾害反转以及灾难后的可视化建模。毫无疑问，未来海洋科学技术竞赛必将汇聚到海洋数据探索中。另一方面，海洋大数据还给数据管理带来了许多新挑战，例如数据捕获，存储，分析和应用程序的困难以及数据质量控制和数据安全性。为了突出海洋大数据的理论方法和实际应用，本文阐述了有关海洋大数据及其管理的广泛观点，对关键方法和模型进行了调查，介绍了一个工程实例来演示管理体系结构，并讨论了现有的挑战。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第11期|384742.1-384742.13|共13页
  • 作者

    Huang Dongmei; Zhao Danfeng; Wei Lifei; Wang Zhenhua; Du Yanling;

  • 作者单位

    Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China.;

    Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China.;

    Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China.;

    Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China.;

    Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China.;

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