Automatic Monitoring Method for Surface Deformation of Coastal Area Based on Time Series Analysis

Abstract

ABSTRACT Liu, L.; Wang, C.; Zhang, H.; Tang, Y., and Zhang, Z., 2019. Automatic monitoring method for surface deformation of coastal area based on time series analysis. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 194–199. Coconut Creek (Florida), ISSN 0749-0208. The surface deformation monitoring in coastal areas is affected by the uncertainty of flow control, which leads to the low accuracy of surface deformation monitoring. In order to improve the accuracy of surface deformation monitoring in coastal areas, an automatic monitoring method of surface deforma tion in coastal areas based on time series analysis is proposed. The big data structure model of surface deformation in coastal areas is constructed, and the distributed information reconstruction of surface deformation in coastal areas is carried out by using phase space reconstruction and correlation coefficient mining methods. Big data fusion cluster analysis of surface deformation in coastal areas is carried out combined with time series analysis method. The dynamic distribution characteristics of surface deformation big data in coastal areas are extracted, and the clustering and information fusion results of surface deformation characteristics in coastal areas are obtained. The automatic monitoring of surface deformation dynamics in coastal areas is realized. The simulation results show that the accuracy of automatic monitoring of surface deformation in coastal areas is high, and the average confidence level of monitoring is better than that of traditional methods, which improves the adaptability of surface deformation monitoring in coastal areas.