Journal
JOURNAL OF MARINE SCIENCE AND ENGINEERING
Volume 7, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/jmse7090312
Keywords
breakwater; extreme learning machine; stability assessment; machine learning
Categories
Funding
- National Natural Science Foundation of China [51520105014]
- Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX19_ 2328]
- National Key R&D Program of China [2016YFC0402108, 2017YFC0405900]
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The stability number of a breakwater can determine the armor unit's weight, which is an important parameter in the breakwater design process. In this paper, a novel and simple machine learning approach is proposed to evaluate the stability of rubble-mound breakwaters by using Extreme Learning Machine (ELM) models. The data-driven stability assessment models were built based on a small size of training samples with a simple establishment procedure. By comparing them with other approaches, the simulation results showed that the proposed models had good assessment performances. The least user intervention and the good generalization ability could be seen as the advantages of using the stability assessment models.
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