Zhao, J.; Yu, J., and Wang, X., 2020. Research on systematic risk early warning system based on machine learning technology: A case study of marine economy. In: Yang, D.F. and Wang, H. (eds.), Recent Advances in Marine Geology and Environmental Oceanography. Journal of Coastal Research, Special Issue No. 108, pp. 230–233. Coconut Creek (Florida), ISSN 0749-0208.

With the rapid development of information technology, the value contained in big data has attracted more and more attention. Conducting efficient analysis of big data has become an important topic. Machine learning is one of the commonly used methods for data analysis. The traditional machine learning algorithm is often designed as the way of offline batch training. However, this method is not suitable for data sets with massive scale and continuous growth in the big data environment. Transforming the traditional machine learning algorithm so that it can better apply to the big data environment has become a research hotspot. With the rapid development of economy and society and the continuous progress of science and technology, the public's understanding of ocean functions is gradually deepened, the demand for marine products and services is increasing every day, and the economic and social benefits of the ocean are continuously rising. In this context, great importance should be given to the examination of marine resources and environment, the development and utilization of work, the constant adjusting of the ocean economic development policy, and the variety of comprehensive marine management measures to ensure the sustainable development of implementation of marine programs. The current mainstream of machine learning technology based on the marine economy of systemic risk early warning system for research is proposed here.