碩士 / 國立高雄海洋科技大學 / 海事資訊科技研究所 / 104 / Taiwan Ocean Research Institute (TORI) established the Taiwan Ocean Radar Observing System (TOROS) based on the CODAR high frequency surface wave radar (HFSWR). The current data from the "Taiwan Ocean Radar Observing System" are employed to study the currents in the Bashi Channel. However, the quality and applicability of the ocean surface current data results will be affected substantially if there exist missing values in the database. So it has important significance and great applied value to fill missing data. In this study, both the interpolation method and artificial neural network methods were used for HFSWR ocean surface current data imputation. The ocean surface current data over the past six month (from 2014/7/1 to 2014/12/31) in the Bashi Channel have collected for this study. In order to improve the applicability of HFSWR ocean surface current data, a short term data filling model using artificial neural network (ANN) was developed in this study. The optimum structure of the present ANN model for each ocean current grid is set up from examining the learning rate, input parameters, numbers of hidden layer, learning times and input data length.
| Identifer | oai:union.ndltd.org:TW/104NKIM0297001 |
| Date | January 2015 |
| Creators | Ren-Feng Liao, 廖人鋒 |
| Contributors | Chih-Min Hsieh, Jian-Wu Lai, 謝志敏, 賴堅戊 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 88 |
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