Please use this identifier to cite or link to this item:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17095
Title: | 增進時序資料預測效能之一般化模型 A General Framework for Enhancing Prediction Performance on Time Series Data |
Authors: | Chin-Hui Chen 陳晉暉 |
Advisor: | 鄭卜壬 |
Keyword: | 時序資料,時間序列,預測模型, Time Series Data,Time Series Prediction,Framework, |
Publication Year : | 2013 |
Degree: | 碩士 |
Abstract: | Traditionally, researchers apply the latest data to predict the near future of Time Series Data prediction. However, we proposed a novel framework to use not only latest data but also potential accurate predicted results. And it also be able to predict much further results for enhancing the prediction. The framework adopts generic predict methods and extract specific features ac- cording to the data property. Three type of feature sets are designed to capture the Statistic, Reliability and Periodicity of the Time Series Data. Short-Term and Long-Term Prediction Enhancement algorithms are also introduced to im- prove the prediction performance. The experiments show that Short-Term En- hancement increases the accuracy of +20.04% and Long-Term Enhancement +9.59% compared to well-known baseline approaches, ARIMA and HW-ES. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17095 |
Fulltext Rights: | 未授權 |
Appears in Collections: | 資訊工程學系 |
Files in This Item:
File | Size | Format | |
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ntu-102-1.pdf Restricted Access | 1.82 MB | Adobe PDF |
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