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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/119969

    Title: 運用監督式學習於氣象觀測時序資料之自動異常偵測
    Supervised Learning-Based Anomaly Detection of Meteorological Time Series Data
    Authors: 李韋霆
    Lee, Wei-Ting
    Contributors: 沈錳坤
    Shan, Man-Kwan
    Lee, Wei-Ting
    Keywords: 異常偵測
    Date: 2018
    Issue Date: 2018-09-03 16:02:28 (UTC+8)
    Abstract: 近年來氣候變遷是全球所關注的重要議題,各種極端氣候的現象也不斷增多,對於氣候監測與預報的服務需求與日俱增,氣象觀測數據的正確性,更顯得重要。若能及時的進行資料檢核,有效的剔除不合理的數據,提升觀測資料的品質,對於氣象預報作業有相當大的助益。
    Recently, climate change is a global issue of concern. Extreme weather events are increasing. The service requests of climate monitoring and forecasts are increasing as well. The accuracy of meteorological data is crucial. If the data are promptly checked and the unreliable data are effectively removed to enhance the quality of the observation data, it will benefit the weather forecasting operations.
    To strengthen the procedure of data inspection, the study adopted the data over the past five years from the weather observation stations affiliated with the Central Weather Bureau, including manned and automatic weather stations to automatically detect anomalies in real-time observation data by using the theory and techniques of data mining. The result of the study can be coordinated with the inspection system of the Central Weather Bureau to develop appropriate data processing procedures, which can enhance the efficiency of the real-time inspection and allow information to be applied in the following weather forecasts and analysis.
    By means of the approach of supervised learning, the study utilized the inspection data from the manned weather stations as well as the data from the adjacent observation stations to establish an anomaly detection model through space-time data processing. The study indicated that a certain level of inspection capabilities on the weather factors of temperature and relative humidity could reduce the follow-up time for human intervention and eliminate the unreliable data more efficiently.
    The weather observation data which are checked through the inspection system can not only support weather professionals in weather analysis and forecasting operations but also be provided for value-added application services in various industries, which will benefit different fields and operation application.
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    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0101971009
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.EMCS.008.2018.B02
    Appears in Collections:[資訊科學系碩士在職專班] 學位論文

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