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dc.contributor.author張憲國zh_TW
dc.contributor.authorHsien-Kuo, Changen_US
dc.date.accessioned2016-03-28T08:17:46Z-
dc.date.available2016-03-28T08:17:46Z-
dc.date.issued2015en_US
dc.identifier.govdocMOTC-IOT-104-H2EB001fzh_TW
dc.identifier.urihttp://hdl.handle.net/11536/130424-
dc.identifier.urihttps://www.grb.gov.tw/search/planDetail?id=11418275&docId=460315en_US
dc.description.abstract交通部運輸研究所港灣技術研究中心已在臺北港外海設置一個觀測樁,同時測量波浪與風速,波浪以觀測樁水下-5m及-10m處各安裝無線電傳輸之潮波流儀來觀測,在觀測樁之海面上10m處有自記式之風速儀。本計畫主要探討風速及波浪資料的統計特性,並建立兩者間之關係。 本計畫前期比較過海上與陸上測站風速特性,並探討向岸風與離岸風速之時間分布特性,並建立各區風向的風浪推算的經驗公式。最後分析風速其的持續,在考慮波能傳遞及損失下,建立逐時的波浪推算模式。 本年度計畫主要工作項目為(1)探討湧浪的特性;(2)根據風向的持續性提出合適區分向離岸風與季節風的指標;(3)建立單點及多點的回歸的波浪推算模式;(4) 建立單點及多點的回歸的適應性類神經模式。本研究結果未來應用當為臺北港即時預報波浪系統的推算方法。zh_TW
dc.description.abstractA field observation pole for simultaneously measuring waves and winds at offshore seas of the Taipei harbor was set up by Harbor and Marine Technology Center. Two ADCPs below 5 and 10m from mean sea level are used to measure waves and currents and automatic-record anemometer is used to observe wind speed and wind direction at 10m high above seas. The project is to investigate the statistic properties of the wind and wave hourly data for 2010 and 2012 and to establish the relationship between both wind and wave data. In the early study of this three-year project, a comparison of wind distribution statistics at the pole and that at the tip of northern breakwater of the Taipei Harbor is made to study the difference of monthly and seasonal statistics. Onshore and offshore winds are classified from all wind data. The relationship between wave heights as well as periods and winds for each of four groups are established by regression analysis. Based on wind persistence, two wave forecasting models were developed for given initial wave height and subsequent wind speed. Four aims of this year project are (1) to investigate the properties of swell; (2) to propose a classification of onshore and offshore winds and seasonal winds based on wind persistence; (3) to establish a wave forecasting model from winds at single point or multi-points by regression analysis; (4) to establish a wave forecasting model from winds at single point or multi-points by adaptive neuro-fuzzy inference system, ANFIS. The results can be used for a fast forecasting wave system in the future.en_US
dc.description.sponsorship交通部運輸研究所zh_TW
dc.language.isozh_TWen_US
dc.subject臺北港zh_TW
dc.subject風與波浪zh_TW
dc.subject統計特性zh_TW
dc.subjectTaipei Harboren_US
dc.subjectWinds and Wavesen_US
dc.subjectStatistical Correlationen_US
dc.title104年臺北港風與波浪關連性之統計特性研究zh_TW
dc.titleStatistical relationship on between winds and waves at the Taipei Harbor (2015)en_US
dc.typePlanen_US
dc.contributor.department國立交通大學{土木工程研究所}zh_TW
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