| 姓名 | 張玉瑛(Yu-Ying Chang) | 電子郵件信箱 | owl501@yahoo.com.tw | |
| 畢業系所 | 營建工程系碩士班(Department and Graduate Institute of Constrction Engineering) | |||
| 畢業學位 | 碩士(Master) | 畢業時期 | 95學年第2學期 | |
| 論文名稱(中) | 以支援向量機預測台灣地區營造工程物價指數之研究 | |||
| 論文名稱(英) | Forecasting the Trend of Construction Cost Indices for Taiwan with Employing Support Vector Machine | |||
| 檔案 |
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論文使用權限 | 校內外都二年後公開 | |
| 論文語文/頁數 | 中文/86 | |||
| 摘要(中) | 「營造工程物價指數」（Construction Cost Indices, CCI）是台灣地區營造業經濟指標之一，由於為事後統計之數值，如果能準確的預知未來指數的趨勢，必能降低營建物價波動對營造業造成之風險。本研究利用「支援向量機」（Support Vector Machine, SVM）做為預測工具，其不需先提供充足的資訊範圍及預設任何的假設，且正確性不易受到資料量大小之限制；並於預測模型中納入影響經濟環境的變數，使得預測模式在經濟環境改變時，仍保有其正確性。研究結果發現，於有限的資料樣本中加入經濟環境的變數，藉由「支援向量機」所建立之模型，可作出與實際指數趨勢相當的預測結果，證明本文所採用的方法之適用性與正確性。 | |||
| 摘要(英) |
Construction Cost Indices (CCI), one of the economic indicators
for Taiwan's construction industry, is a subsequent numerical
statistics. If the trend of the CCI can be forecasted, the risk
of price fluctuations in the construction industry can be reduced positively. In this study, support vector machine (SVM) is employed to predict the trend of CCI. From the results, the developed SVM model demonstrates that the method does correctly predict the tendency of CCI in a specified interval with the limited information. Those variables affecting the economic environment are also included in the developed SVM model such that the prediction retains the validity when the economic environment changes. In the thesis, we found out that with the limited samples, the model made with SVM can correctly fit the actual index trend. The results shown in the thesis demonstrate the applicability and accuracy of the developed approach used in this study. |
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| 口試日期 | 2007-06-25 | 繳交日期 | 2007-08-15 | |