Neural network with multi-trend simulating transfer function for forecasting typhoon wave
| dc.citation.epage | 194 | en_US |
| dc.citation.issue | 3 | en_US |
| dc.citation.spage | 184 | en_US |
| dc.citation.volume | 37 | en_US |
| dc.citation.woscount | 8 | |
| dc.contributor.author | Chang, HK | en_US |
| dc.contributor.author | Chien, WA | en_US |
| dc.contributor.department | 土木工程學系 | zh_TW |
| dc.contributor.department | Department of Civil Engineering | en_US |
| dc.date.accessioned | 2014-12-08T15:17:12Z | |
| dc.date.available | 2014-12-08T15:17:12Z | |
| dc.date.issued | 2006-03-01 | en_US |
| dc.description.abstract | This study develops an NN typhoon wave model to accurately and efficiently calculate wave heights at a point of interest. Multi-trend simulating transfer functions were first introduced to exemplify the relationship between wave heights and each conceivable input factor by regressive fitting. The proposed NN-MT model can accurately forecast wave peak with an error of less 1.2 m and with time delay within 3 h and can be extended to cover the station besides the original station of interest. (C) 2005 Elsevier Ltd. All rights reserved. | en_US |
| dc.identifier.doi | 10.1016/j.advengsoft.2005.05.001 | en_US |
| dc.identifier.issn | 0965-9978 | en_US |
| dc.identifier.journal | ADVANCES IN ENGINEERING SOFTWARE | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1016/j.advengsoft.2005.05.001 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/12552 | |
| dc.identifier.wosnumber | WOS:000235690500005 | |
| dc.language.iso | en_US | en_US |
| dc.subject | neural network wave model | en_US |
| dc.subject | trend simulation | en_US |
| dc.subject | transfer function | en_US |
| dc.subject | peak wave height | en_US |
| dc.title | Neural network with multi-trend simulating transfer function for forecasting typhoon wave | en_US |
| dc.type | Article | en_US |