碩士 / 嘉南藥理大學 / 觀光事業管理系 / 103 / The administration of hot spring in Taiwan has collected and checked the data of hot spring level these years. Unique temperature and quality of the hot spring usually cause the device recorded any missing data. The data analysis used the gray theory in order to supplement the data of hot spring level.
This study based on Lih Huey Kang’s observation of using whole data of hot spring level, tested and predicted the best model with gray prediction. The best model helped the fragmented part of data fixed, which arranged to produce the complete set of data. In the data of hot spring level in Jiaosi, the data of Hot Spring Park, Guo-Xiao and Tai-Tzu station fixed the four batches of the fragmented data using the best model estimation.
The result show the predicted deviation appeared in these conflicting data, the error of the predicted deviation would increase with time. The reason that caused these errors of posterior is the anterior, and the trend of the deviation increased or decreased in the system of gray prediction. To prevent these errors, divergence distance method was needed.
This study used the best model in each administrations of hot spring. The action made the fragmented data of hot spring level, which included Shin Xiao Shen Station、Shin Xiao Chien Station、Tourist Center Station、Fu Chong Station and Da Zhong Rd. Station during 2011~2014 fixed. The result of the supplementation brought down the gap between the actual hot spring levels in Jiaosi.
| Identifer | oai:union.ndltd.org:TW/103CNUP0517024 |
| Date | January 2015 |
| Creators | Ming Hui Cheng, 鄭茗鏸 |
| Contributors | Jumg Wei Chen, 陳忠偉 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 123 |
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