歷史性建築的保存被世界各國視為一項重要的工作，基於其文化、社會、經濟與都市更新的潛在效益。在有限的時間之下，準確的預算分配是影響歷史建築修復的關鍵因素。無效的經費評估機制常導致歷史建築損壞程度的增加。因此，本研究以案例式推演(CBR)的方法概念，建構新的修復經費評估模式，試圖取代過去專家評估的方式。在CBR的評估模式中，運用了「誘導式索引」與「最近搜尋法」兩種萃取技術，從知識庫中挑選出適當的建議案例。最後，以兩種歷史建築類型進行案例試驗，並探討操作的結果。其結果顯示藉由CBR的模擬可有效預測新案例的實際修復經費，故解決了變更設計的問題、縮小經費不一致的情況及縮短補助經費審查的時間。此外，此評估模式亦適用於具有相同問題的國家，尤其是位於地震帶區域的周邊。

Historical building conservation is an important work for most global organizations due to its potential cultural, social, economic, and urban renovation benefits. Accurately allocating budget in a limited time is a crucial factor that profoundly affects the restoration of historical buildings. An ineffective cost estimating mechanism often causes further damage to historical buildings which are in facing the demands of urgent restoration. This study presents a new cost estimation model based on the case-based reasoning (CBR) approach instead of a traditionally ways which are the experience from experts. In CBR model, two retrieval techniques, ‘Inductive Indexing’ and ‘Nearest Neighbor’, are then applied to retrieve relevant cases from the knowledge-based database. Two of the most common types of Taiwan historical buildings are tested to explore the restoration cost implications and discuss of the results of case study. The result reveals that the CBR solution can effectively predict the actual restoration cost, solve order change problems, mitigate the difference of the budget and reduce the budget review time. These applications are also useful for many other countries, especially for those seismic belt regions, that are facing similar problems regarding historical building restoration.

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