expanded classification 中文意思是什麼

expanded classification 解釋
擴大分類
  • expanded : adj. 1. 膨脹的；被擴大的；被延伸的；（花瓣）展開的。2. 【印刷】寬體的 （＝extended）。
  • classification : n 1 選別；分等，分級；分選。2 【動、植】分類（法）。 〈分類級別為： phylum 【動物；動物學】及 div...
  1. Fourth, according to the weibull distributing functions of equivalent loads, calculated the max loads by expanded sample method, acquired eight routine loads spectrum of each roads taking advantages of the connover classification method, calculated the respective enhancement coefficient in principle of amended miner linear accumulated fatigue damage rule, by the comparative norm of general tar - paved road, educed the mathematical model of calculating enhancement coefficient of synthesized roads

    利用數理統計的方法得到了各路面的等效載荷的weibull分佈函數。第四，根據各路面的等效載荷的weibull分佈函數採用擴展樣本法求得了各路面的極值載荷，按照connover的分級法得到了各路面的八級程序載荷譜。以一般瀝青公路為比較基準，採用修正的miner線性累積損傷理論，根據前橋的s - n和p - s - n關系式得到了各路面的強化系數，建立了綜合路面的強化系數計算的數學模型。
  2. At first, this thesis described the necessary of implementing dm in crm systems at on the basis of explaining the elementary concepts and principles of crm and dm, constructed a crm system framework with the center of dm. then, it ameliorated and expanded the models of traditional association rule and decision tree for classification, put forward association rule with time constraint and fuzzy decision tree for classification. the thesis amended traditional algorithms and showed the application methods of new models

    論文首先從客戶關系管理和數據挖掘的基本概念和原理入手，闡明了在客戶關系管理中應用數據挖掘的必要性，構建了以數據挖掘為核心的crm系統框架；然後，論文改進和擴展了傳統的關聯規則和決策分類樹模型，提出了具有確定性時間約束的關聯規則和模糊決策分類樹，並修改了傳統的挖掘演算法，通過示例展示了新模型的應用方法。
  3. In building fuzzy decision tree, each expanded attribute ca n ' t classify the class label clearly like decision tree, but the cases covered with the attribute - values have some overlap. so the entire process of building trees is based on a significant level a, the import of a can reduce such overlap in some degree, decrease the uncertainty of classification and improve classification result

    在模糊決策樹的產生過程中，用模糊熵選擇的擴展屬性不能像經典決策樹那樣將類清晰的分開，而是屬性術語所覆蓋的例子之間有一定的重疊，因此樹的整個產生過程在給定的顯著性水平的基礎上進行，參數的引入能在一定程度上減少這種重疊，從而減少分類的不確定性，提高模糊決策樹的分類結果。
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