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題名 | Hybrid Fuzzy-Random Theorem for System Modeling=複合式模糊隨機理論作為系統之模擬 |
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作者 | 張永熙; 趙汝仁; | 書刊名 | 高雄科學技術學院學報 |
卷期 | 28 1998.12[民87.12] |
頁次 | 頁1-9 |
分類號 | 400.24 |
關鍵詞 | 認知性; 模糊性; 隨機性; 迴歸; 系統模擬; 不確定; Cognitive; Fuzzy; Random; Regression; System modeling; Uncertainty; |
語文 | 英文(English) |
中文摘要 | 複合式模糊隨機理論可作為系統模擬之新方法,在系統模擬中必須考慮的不確定 現象種類,一類是屬於認知的,例如系統的模糊現象,另一類是屬於非認知的,例如自然界 的隨機現象;非認知不確定可表示成隨機分佈方程式,認知不確定可用模糊函數來表示;本 文主旨在介紹複合式模糊-隨機理論,同時將認知與非認知不確定考慮在同一系統中,除了 基本理論的探討,在實用上,並以複合式模糊-最小二乘迴歸分析為例,該方法將數據的隨 機性及模糊性同時模擬成一個迴歸方程式,並以數字實例介紹其運算過程,最後作成結論。 |
英文摘要 | A new concept of hybrid fuzzy-random theorem is proposed for system modeling by considering both cognitive and non-cognitive uncertainties. The theorem is used to process fuzzy variables in the traditional probability theory, which only consider therandom aspect in the variables. The non-cognitive uncertainty of a variable can bedescribed by a probability mass or density function (PMF or PDF, respectively). The cognitive uncertainty of a variable can be described by a membership function as used ind fining fuzzy sets. The combined effect of both cognitive and non-cognitiveuncertainties for a variable in risk assessment was modeled using a proposed fuzzy-random PDF. An application of the new theorem, called hybrid fuzzy-least-squares regressionanalysis, is used to model data with fuzziness and randomness into a regression equation. A numerical example is provided to illustrate the computation work. Summary andconclusions are drawn in the end. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。