fuzzy number entropy 中文意思是什麼

fuzzy number entropy 解釋
模糊數熵
  • fuzzy : adj. 1. 有茸毛的,覆著細毛的,如茸毛的。2. 不清楚的。fuzziness n.
  • number : n 1 數;數字;〈pl 〉算術。2 (汽車等的)號碼;第…,第…卷,第…期〈通常略作 No (復數 Nos ),用於...
  • entropy : n. 1. 【物理學】熵。2. 【無線電】平均信息量。
  1. Abstract : according to the theory of difference analysis, this paper proposed using mixed - f statistic to determine the optimal class number of fuzzy cluster, and using fuzzy partition entropy to verify whether the class number is optimal, the optimal class number can be determined by the two statistics mentioned above correctly

    文摘:根據方差分析理論,提出應用混合f統計量來確定最佳分類數,並應用模糊劃分熵來驗證最佳分類數的正確性,綜合運用上述兩個指標可以準確確定最佳聚類數。
  2. Using the f - ahp model algorithms that based on fuzzy number and interval arithmetic solve the multi - attributes and fuzzy problems of agricultural project appraisal. using entropy weight ranking of f - ahp is more efficiency. using a - cut and index of optimism x. estimate the uncertainty and preference of decision makers

    用基於模糊數、區間數運演算法則的f - ahp模型解決了農業項目投資評估的多屬性及模糊性問題;採用熵權使得排序更加科學;通過置信度與樂觀指數考慮了不確定性及決策者的風險態度。
  3. By analyzing expression between a and fuzzy entropy from the view of analytics, this paper analyses the relationship of between a and fuzzy entropy and the changing trend of fuzzy entropy function with the increase of a, then discusses the sensitivity of the parameter a to classification result such as total nodes, rule number, classification accuracy of fuzzy decision tree, proposes an experimental method of obtaining optimal a, it is proved by experiment that the optimal value a obtained by this method can make the classification result of fuzzy decision tree best, and therefore provides the academic evidence of selecting parameter a in order to gain the best classification result

    本文在visualc + +軟體開發平臺及模糊id3演算法的基礎上,從解析的角度出發,通過分析參數與模糊熵之間的函數關系式,討論了隨著的增加,模糊熵函數的變化趨勢,進一步分析了參數對模糊決策樹的分類結果在訓練準確率、測試準確率、規則數等方面所表現出的敏感性,探討了得到最優參數的實驗方法。實驗證明,利用這一方法得到的最優參數的值,可以使模糊決策樹的分類結果達到最好的效果,從而為人們用模糊決策樹進行分類時選取參數以獲得最優的分類結果,提供了良好的理論依據。
  4. According to the theory of difference analysis, this paper proposed using mixed - f statistic to determine the optimal class number of fuzzy cluster, and using fuzzy partition entropy to verify whether the class number is optimal, the optimal class number can be determined by the two statistics mentioned above correctly

    根據方差分析理論,提出應用混合f統計量來確定最佳分類數,並應用模糊劃分熵來驗證最佳分類數的正確性,綜合運用上述兩個指標可以準確確定最佳聚類數。
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