Influence of Regular Wave and Ship Characteristics on Mooring Force Prediction by Data-Driven Model
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f Regular Wave and Ship Characteristics on Mooring Force Prediction by Data-Driven Model LIU Bi-jina, CHEN Xiao-yuna, *, ZHANG You-quanb, XIE Jingc, d, CHANG Jiangc, d a School of Civil Engineering and Architecture, Xiamen University of Technology, Xiamen 361024, China b Fujian Marine Forecasts, Fuzhou 350003, China c Tianjin Research Institute for Water Transport Engineering, Tianjin 300456, China d Tianjin Survey and Design Institute for Water Transport Engineering, Tianjin Key Laboratory of Surveying and Mapping
for Waterway Transport Engineering, Tianjin 300456, China Received August 13, 2019; revised March 24, 2020; accepted April 25, 2020 ©2020 Chinese Ocean Engineering Society and Springer-Verlag GmbH Germany, part of Springer Nature Abstract The study of mooring forces is an important issue in marine engineering and offshore structures. Although being widely applied in mooring system, numerical simulations suffer from difficulties in their multivariate and nonlinear modeling. Data-driven model is employed in this paper to predict the mooring forces in different lines, which is a new attempt to study the mooring forces. The height and period of regular wave, length of berth, ship load, draft and rolling period are considered as potential influencing factors. Input variables are determined using mutual information (MI) and principal component analysis (PCA), and imported to an artificial neural network (NN) model for prediction. With study case of 200 and 300 thousand tons ships experimental data obtained in Dalian University of Technology, MI is found to be more appropriate to provide effective input variables than PCA. Although the three factors regarding ship characteristics are highly correlated, it is recommended to input all of them to the NN model. The accuracy of predicting aft spring line force attains as high as 91.2%. The present paper demonstrates the feasibility of MI-NN model in mapping the mooring forces and their influencing factors. Key words: mooring force, characteristics of ship, neural network, mutual information, principal component analysis Citation: Liu, B. J., Chen, X. Y., Zhang, Y. Q., Xie, J., Chang, J., 2020. Influence of regular wave and ship characteristics on mooring force prediction by data-driven model. China Ocean Eng., 34(4): 589–596, doi: https://doi.org/10.1007/s13344-020-0053-1
1 Introduction With the development of coastline and deep-water port, safe operation of ships and offshore platform is attracting more attention. The study of mooring forces with large open moored ships can improve the stability of mooring conditions, reduce the cable-breaking accidents and provide necessary data for wharf design. Since the ships are exposed to complex hydrology and meteorology conditions, the measurement of mooring forces is difficult and dependents on many variables. Research of mooring forces is mainly based on physical model tests (Chu et al., 2014; Cornett, 2014; Rosa-Santos et al., 2014; Sande et al., 2019) and numeri
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