本研究以臺北市內湖區白石湖吊橋中央撓度監測為研究對象，依據過去近10年的每月監測109筆數據，利用其中104筆採用Python的statsmodels時間序列分析與預測，再利用5筆資料驗證，時間序列分解方法包含經典分解(加法與乘法模型) CLASSICAL DECOMPOSITION及STL DECOMPOSITION分解模型作分析，再利用簡單移動平均線（SMA）、加權移動平均線（WMA）、指數移動平均線 (EMA)、STL進行預測(EMA)作預測，將分析與預測結果作討論與建議。

In this study, the central deflection monitoring of the Baishihu Suspension Bridge in Neihu District, Taipei City was used as the research object. Based on 109 monthly monitoring data in the past, 104 of them were analyzed and predicted using statsmodels using Python for time series analysis and prediction. The five data was used for verification and time series decomposition. The methods include CLASSICAL DECOMPOSITION classic decomposition (addition and multiplication model) and STL DECOMPOSITION decomposition for analysis, and then use simple moving average (SMA) prediction, weighted moving average (WMA), exponential moving average (EMA), STL for prediction ( EMA) makes predictions, and discusses and recommends the results of analysis and prediction.