Wei, X. and Qin, C., 2019. Risk early-warning model of ocean international trade based on SVM. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 785–790. Coconut Creek (Florida), ISSN 0749-0208.

In order to reduce the risk of marine international trade waybill and improve the ability of risk early warning, an automatic early warning model of marine international trade waybill risk based on SVM theory is proposed. The panel data statistical regression analysis technology is used to detect the risk characteristic information of marine international trade waybill. According to the detection results, the risk data characteristics of marine international trade waybill risk early warning model are analyzed, sampled and integrated, the big data information characteristic quantity associated with marine international trade waybill risk is excavated, and the least square estimation method is used to automatically assess the risk of marine international trade waybill. The association rule set and rough quantitative feature set of marine international trade waybill risk big data are extracted, and the robustness test and automatic prediction of marine international trade waybill risk assessment are carried out with the method of piecewise regression analysis, so as to realize the automatic early warning of marine international trade waybill risk. The simulation results show that the model can accurately predict the risk of marine international trade waybill, the accuracy of early warning is high, and the robustness of marine international trade waybill risk early warning is good.