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  1. National Taiwan Ocean University Research Hub
  2. 海洋科學與資源學院
  3. 海洋環境資訊系
Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/10911
DC FieldValueLanguage
dc.contributor.authorChih-Chiang Weien_US
dc.date.accessioned2020-11-21T06:54:20Z-
dc.date.available2020-11-21T06:54:20Z-
dc.date.issued2014-12-01-
dc.identifier.issn0882-8156-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/10911-
dc.description.abstractThe purposes of this study were to forecast the hourly typhoon wind velocity over the Penghu Islands, and to discuss the effects of the terrain of the Central Mountain Range (CMR) of Taiwan over the Penghu Islands based on typhoon tracks. On average, a destructive typhoon hits the Penghu Islands every 15–20 yr. As a typhoon approaches the Penghu Islands, its track and intensity are influenced by the CMR topography. Therefore, CMR complicates the wind forecast of the Penghu Islands. Six main typhoon tracks (classes I–VI) are classified based on typhoon directions, as follows: (I) the direction of direct westward movement across the CMR of Taiwan, (II) the direction of northward movement along the eastern coast of Taiwan, (III) the direction of northward movement traveling through Taiwan Strait, (IV) the direction of westward movement traveling through Luzon Strait, (V) the direction of westward movement traveling through the southern East China Sea (near northern Taiwan), and (VI) the irregular track direction. The adaptive network-based fuzzy inference system (ANFIS) and multilayer perceptron neural network (MLPNN) were used as the forecasting technique for predicting the wind velocity. A total of 49 typhoons from 2000 to 2012 were analyzed. Results showed that the ANFIS models provided high-reliability predictions for wind velocity, and the ANFIS achieved more favorable performance than did the MLPNN. In addition, a detailed discussion on the interaction of the CMR with the Penghu Islands based on various track directions is provided. For class I, the CMR is observed to have significantly influenced variations in wind speed when typhoons approached the Penghu Islands. In addition, the winds on the Penghu Islands were observed to have been influenced by the distance from the typhoon center to the Penghu Islands for all classes except class II.en_US
dc.language.isoenen_US
dc.relation.ispartofWeather and Forecastingen_US
dc.subjectForecastingen_US
dc.subjectModel evaluation/performanceen_US
dc.subjectNeural networksen_US
dc.subjectWind effectsen_US
dc.titleSurface Wind Nowcasting in the Penghu Islands Based on Classified Typhoon Tracks and the Effects of the Central Mountain Range of Taiwanen_US
dc.typejournal articleen_US
dc.identifier.doi<Go to ISI>://WOS:000346348800011-
dc.identifier.doi<Go to ISI>://WOS:000346348800011-
dc.identifier.doi10.1175/waf-d-14-00027.1-
dc.identifier.doi<Go to ISI>://WOS:000346348800011-
dc.identifier.doi<Go to ISI>://WOS:000346348800011-
dc.identifier.url<Go to ISI>://WOS:000346348800011
dc.relation.journalvolume29en_US
dc.relation.journalissue6en_US
dc.relation.pages1425–1450en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextno fulltext-
item.grantfulltextnone-
item.openairetypejournal article-
crisitem.author.deptCollege of Ocean Science and Resource-
crisitem.author.deptDepartment of Marine Environmental Informatics-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.deptCenter of Excellence for Ocean Engineering-
crisitem.author.deptData Analysis and Administrative Support-
crisitem.author.orcid0000-0002-2965-7538-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Ocean Science and Resource-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCenter of Excellence for Ocean Engineering-
Appears in Collections:海洋環境資訊系
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