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Estimation of Design Sea Ice Thickness with Maximum Entropy Distribution by Particle Swarm Optimization Method

Estimation of Design Sea Ice Thickness with Maximum Entropy Distribution by Particle Swarm Optimization Method

作     者:TAO Shanshan DONG Sheng WANG Zhifeng JIANG Wensheng 

作者机构:College of Engineering Ocean University of China College of Environmental Science and Engineering Ocean University of China 

基  金:supported by the National Natural Science Foundation of China (Nos. 51279186, 51479183, 51509227) the Shandong Province Natural Science Foundation, China (No. ZR2014EEQ030) the Fundamental Research Funds for the Central Universities (No. 201413003) 

出 版 物:《Journal of Ocean University of China》 (中国海洋大学学报(英文版))

年 卷 期:2016年第15卷第3期

页      码:423-428页

摘      要:The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.

主 题 词:sea ice thickness maximum entropy distribution particle swarm optimization return period offshore structural de-sign 

学科分类:07[理学] 0707[理学-海洋科学类] 08[工学] 081202[081202] 0812[工学-测绘类] 

核心收录:

D O I:10.1007/s11802-016-2821-3

馆 藏 号:203168529...

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