Wave Height Interval Distribution Method Based on Nonlinear Shallow Water Wave Function

Abstract

Li, X.; Zhao, Y., and Jin, H., 2020. Wave height interval distribution method based on nonlinear shallow water wave function. 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. 843–846. Coconut Creek (Florida), ISSN 0749-0208.In order to improve the ability to analyze and judge the interval distribution of wave height, it is necessary to estimate the interval distribution of wave height. An interval distribution estimation method of wave height based on nonlinear shallow water wave function is proposed. A statistical time series analysis model for estimating the interval distribution of sea wave height is constructed, large data mining and feature extraction for estimating the interval distribution of sea wave height are carried out by adopting a large data feature detection method, ordered clustering of statistical feature sequences of the interval distribution of sea wave height is carried out based on a nonlinear shallow water wave function estimation idea, information clustering and attribute merging in the process of estimating the interval distribution of sea wave height are carried out by combining a fuzzy C-means clustering analysis method. The feature quantity of association rules of statistical time series of wave height interval distribution is extracted, and the association rule set of statistical time series of wave height interval distribution is analyzed by using principal component analysis method, so as to realize accurate estimation of wave height interval distribution quantity in weighted Markov chain. The simulation results show that the method has high accuracy in estimating the interval distribution of wave height and improves the quantitative analysis capability of the interval distribution of wave height.