企業倚賴資訊的程度與日俱增，資訊系統如因天災人禍導致系統服務中斷，勢必會對企業造成營運損失，因此，災害復原規劃(Disater Recovery Plan，DRP)已成為各企業必須面臨的重要課題。但如何規劃 DRP 牽涉到經驗及案例，要考慮的因素很多，比一般的系統需求如資料庫系統規劃複雜。DRP過去大部份依據專家的知識與經驗來規劃，容易造成規劃品質不一，經驗無法傳承，為解決此問題，本論文將比較災害復原規劃與系統生命週期理論間的差異，提出一個規則及案例知識來表達DRP，並發展一個結合規則式推理(RBR)及案例式推理(CBR)優點的 DRP推理法則雛形系統。我們以兩個實際專家案例來驗證我們的 DRP 知識表達與推理方法，結果顯示，本研究系統可依據使用者需求提供近似專家建議DRP的方案。 Businesses rely on the information more deeply day by day. If information system service interrupts due to disasters, it will make business operation loss. So, disaster recovery plan has become the critical issue that businesses must face. But how to plan DRP has been related to experiences and case study about it. Because there are many issues that must be considered, DRP is more complex than database plan. In previous stage, DRP was planned according to expert’s knowledge and experiences. It will be easy to make the plan’s quality inconsistent and experiences will not be transferred and retained. To resolve the problem, we will compare the difference between System Development Life Cycle and DRP. We will propose a rule and case knowledge representation for DRP, and then develop a hybrid rule and case’s DRP inference protype system with both advantages. At last, we use two practical experts’ cases to validate our DRP knowledge and inference method. The result shows the research system can provide the similar expert’s solution according to the user’s requirement.
