Wang, B., 2020. Early warning method of marine products network marketing risk based on BP neural network algorithm. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 177–181. Coconut Creek (Florida), ISSN 0749-0208.

In order to reduce the early-warning error of marine products network marketing risk, BP neural network algorithm is used to optimize the early-warning method of network marketing risk. According to the structure of BP neural network, the risk early-warning model of seafood network marketing is constructed, and the risk early-warning indicators are set up under the model. This paper analyzes the mechanism of the network marketing risk. Under the risk early warning model, the BP neural network algorithm is used to train the input value of the network marketing and to judge the risk. Finally, the output results of the algorithm are compared with the set warning level to show the early warning results of seafood online marketing risks. Through the contrast experiment with the traditional early warning method, it is found that applying BP neural network algorithm to the risk early warning method of seafood network marketing can effectively reduce the error by 99.8%.