| 摘要: | 對軟體發展中各個階段的風險問題，並無適當的方法予以量化以注入成本中，因而 延誤時程、成本增加、效能不足、與維護不佳等困擾。有鑑於此，我們曾於1996 年【Fuzzy Sets and Systems, Vol. 79 (1996), 323-336; Vol. 80 (1996), 261-271】建構一軟體發展風險評 估之架構模式，而且提出模糊環境下處理整體風險率之演算法；於1999 年【Information Sciences, Vol.113,(1999),301-311】提出一般化的群體評估模式的演算法；於2003 年 【Information Sciences, Vol. 153 (2003), 177-197】提出一整體風險率新的演算法；於2004 年【International Journal of Reliability, Quality and Safety Engineering, Vol. 11 No. 2, (2004), 17-33】提出另一種群體評估整體風險率模式的演算法；於2007 年【WSEAS Transactions on Systems, Issue 9, Vol. 6, (2007), 1270-1275】提出另一種評估整體風險率模式的演算法。 本研究中我們將證明除了等腰三角形的模糊數外，用具符號距離法(Signed distance)解模糊化比用重心法(Centroid) 解模糊化為佳；同時本研究亦將建構一符合 人類思想的模糊語言系列的評估表，並另提出提一個新演算法。本演算法不僅可評判各 個Attribute 的風險率，及整體風險率，亦可針對每個Attribute 中各個模糊語言進行 整體評分，亦可針對整體中各個模糊語言進行評判。 經由演算的結果，我們將提一有 關整體評估的命題。 經由本研究所提的一符合人類思想的模糊語言系列的評估表及新演算法，我們亦可 由群體專家評估軟體發展整體風險率。又者本研究所提的新演算法，將比我們在之前所 提者及S. M. Chen 教授所提者【Fuzzy Sets and Systems, Vol. 118 (2001), 75-88】 【Fuzzy Sets and Systems, Vol. 80 (1996), 261-271】更為方便，且更符合人類思 想。
During the past decades, computer technologies have changed so fast that the need of large software system becomes much more intensive. Since most of the cost evaluations are characterized by high uncertainty, there are many problems occur in the software system development life cycle, such as postponed schedule, increased cost, inefficiency and abandonment. In 1996, we presented a hierarchical structure model of aggregative risk in software development and proposed an algorithm to tackle the rate of aggregative risk [H.-M. Lee, Fuzzy Sets and Systems 79 (3) (1996) 323-336]. Also, in 1996, we presented two algorithms of the group decision making to tackle the rate of aggregative risk in the software development [H.-M. Lee, Fuzzy Sets and Systems 80 (3) (1996) 261-271]. In 1999, we presented an algorithm to evaluate the rate of aggregative risk for the group decision makers with crisp or fuzzy weights [H.-M. Lee, Information Sciences 113 (1999) 301-311]. In 2003, we presented a new algorithm to tackle the rate of aggregative risk [H.-M. Lee et al. Information Sciences, Vol. 153 (2003), 177-197]. In 2004, we presented a group evaluators to evaluate rate of the aggregative risk [H.-M. Lee et al., International Journal of Reliability, Quality and Safety Engineering, Vol. 11 No. 2, (2004), 17-33]. In 2007, we presented a new algorithm to tackle the aggregative risk rate [WSEAS Transactions on Systems, Issue 9, Vol. 6, (2007), 1270-1275]. In this study, we’ll present that the difuzzification by the signed distance is better than by the centroid, except the isosceles triangular fuzzy number. Also, we’ll not only build up a hierarchical structured model of aggregative risk with fuzzy linguistics to meet the human thinking and feeling but also propose a new algorithm to evaluate the rate of aggregative risk in a fuzzy environment by fuzzy sets theory during any phase of the life cycle. Via the proposed algorithm, we’ll propose a proposition which can tackle the grade of linguistic for the attribute, the grade of linguistic for the aggregative model, overall appraisal of each attribute, and overall appraisal of the aggregative risk. Due to the proposed new structured evaluating model meets the human thinking and feeling, the propose algorithm is more efficient than the ones they have presented before (H.-M. Lee, Fuzzy Sets and Systems 79 (3) (1996) 323-336, 80 (3) (1996) 261-271; Information Sciences 113 (1999) 301-311, Vol. 153 (2003), 177-197) and (S. M. Chen, Fuzzy Sets and Systems 118 (2001) 75-88). |
