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DC Field | Value | Language |
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dc.contributor.author | Kundapura S. | |
dc.contributor.author | Hegde A.V. | |
dc.date.accessioned | 2020-03-31T14:22:12Z | - |
dc.date.available | 2020-03-31T14:22:12Z | - |
dc.date.issued | 2017 | |
dc.identifier.citation | Ocean Systems Engineering, 2017, Vol.7, 2, pp.75-87 | en_US |
dc.identifier.uri | 10.12989/ose.2017.7.2.075 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/13976 | - |
dc.description.abstract | A breakwater has always been an ideal option to prevent shoreline erosion due to wave action as well as to maintain the tranquility in the lagoon area. The effects of the impinging wave on the structure could be analyzed and evaluated by several physical and numerical methods. An alternate approach to the numerical methods in the prediction of performance of a breakwater is Artificial Intelligence (AI) tools. In the recent decade many researchers have implemented several Artificial Intelligence (AI) tools in the prediction of performance, stability number and scour of breakwaters. This paper is a comprehensive review which serves as a guide to the current state of the art knowledge in application of soft computing techniques in breakwaters. This study aims to provide a detailed review of different soft computing techniques used in the prediction of performance of different breakwaters considering various combinations of input and response variables. © 2017 Techno-Press, Ltd. | en_US |
dc.title | Current approaches of artificial intelligence in breakwaters - A review | en_US |
dc.type | Review | en_US |
Appears in Collections: | 5. Miscellaneous Publications |
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