查詢結果分析
相關文獻
- 模糊資料之聚類分析
- Minimum AFI for CSP-1 Plan Based on Fuzzy Optimization
- 模糊集合論在教育評分等級系統之應用
- 長期性資產購買或租賃模糊投資決策
- 模糊不迷糊
- 應用模糊聚類分析理論模擬具分散式處理理念而移植於行動臺之新交遞控制演算法則
- Classification of Water Masses and Sound-Scattering Layer Biomass in the Waters off Northeastern Taiwan Using a Fuzzy Clustering Method
- Graded Mean Integration Representation of Generalized Fuzzy Number
- Bayesian Average Outgoing Quality Limit Sampling Plans Based on Fuzzy Optimization
- An Image Understanding System Designed for Feeling the Weather State from an Image
頁籤選單縮合
題 名 | 模糊資料之聚類分析=Fuzzy Clustering with Fuzzy Data |
---|---|
作 者 | 劉大緯; 王小璠; | 書刊名 | 模糊系統學刊 |
卷 期 | 4:2 1998.12[民87.12] |
頁 次 | 頁41-50 |
分類號 | 440.8 |
關鍵詞 | 模糊聚類; 模糊數; 模糊資料; 雙目標模糊c群聚類法; Fuzzy clustering; Fuzzy numbers; Fuzzy data; Bi-objective fuzzy C-means clustering; |
語 文 | 中文(Chinese) |
中文摘要 | 本論文是探討模糊資料之聚類方法,內容重點可分為模型架構與應用說明兩部份 。在模型架構部份,我們提供了一個在 h- 切割下之區間來進行聚類的方法,此方法不僅可 提供這群資料最均質之聚類情形, 也可以了解在其他 h 值下的各種聚類情形,以供比較參 考。實際應用上則以模糊化蝴蝶樣本為例以說明之。 |
英文摘要 | In this study, we proposed a method to solve a general clustering problem of which the data is fuzzy. There are two major parts: one is model-development and the other is a practical application. Regarding the model-development, we extended the Bi-Objective Fuzzy C-means method to the one that can classify fuzzy data by the interval of any h-cut. When we use the proposed method, we can have both the most homogeneous classification as generally desired, and also different clusterings from different h values. For practical application, we used the fuzzified butterfly sample data for illustration. |
本系統中英文摘要資訊取自各篇刊載內容。