Cai, J., 2020. Ship electronic information identification technology based on machine learning. 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. 770–774. Coconut Creek (Florida), ISSN 0749-0208.

Aiming at the problem of low signal accuracy in the traditional electronic information recognition technology which is affected by noise, this paper proposes the research of ship electronic information recognition technology based on machine learning. On the basis of the designed WIFI radio frequency communication circuit, the BP neural network in machine learning technology is used to process the ship electronic information through training and learning. At the same time, the support vector classifier is trained to identify the ship electronic information. The experimental results show that: compared with the traditional ship electronic information recognition technology, the designed ship electronic information recognition technology based on machine learning has less noise in the signal and higher signal accuracy, indicating that the ship electronic information recognition technology based on machine learning is more suitable for the actual ship electronic information recognition.