Zhang, X., 2018. Chart symbol recognition based on computer natural language processing. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 724–728. Coconut Creek (Florida), ISSN 0749-0208.

The precise identification of chart symbol is of great significance for ocean sailing. The current recognition methods for chart symbol have obvious shortcomings in recognition efficiency and control accuracy. To address this problem, it is necessary to discuss the construction and implementation of the grammatical rule of chart symbol language from two aspects of theory and practice. In this paper, the grammatical rule and the essential features of chart symbol language are discussed. The transformation of computer language service mode of chart symbol is achieved. Firstly, the description of various chart symbols is carried out by the computer natural language, and the recognition and processing of chart pattern information are realized. Then based on the data mining technology in computer language, a recognition system for chart symbol is constructed. Finally, based on the computer natural language and the BP neural network information processing method, the precise identification of complex chart symbol is achieved, which better guarantees the safety of ship navigation and provides powerful support for space information service for various marine development and production activities. Simulation results show that the chart symbols recognition method based on computer natural language can effectively realize the noise processing of target symbols, optimize the convergence performance of data processing, and improve the accuracy of chart symbol recognition.

This content is only available as a PDF.
You do not currently have access to this content.