attribute matrix 中文意思是什麼
attribute matrix
解釋
屬性矩陣-
Base on those researches, the thesis applies a madm ( multi attribute decision making ) model. the model embarks from socio - technical viewpoint, analyzes technical issues, economic issues, procedural issues and organizational issues that affect software reengineering, selects economic factors, managemental factors, organizational factors, risk factors and expectational factors as main decision matrix, establishes hierarchy structure of decision matrix
該模型從社會技術系統的觀點出發，分析了技術的、經濟的、程序的和組織政治等因素對軟體再造的影響，提出了用經濟因素、管理因素、組織政治因素、風險因素以及人們對再造后系統的期望等五大類因素作為本決策問題的基本決策因素，並對各類決策因素進行了細分，確立了決策因素的層次結構。 -
Abstract : an integrated approach is proposed to investigate the fuzzy multi - attribute decision - making ( madm ) problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. an eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an madm problem. the simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. finally, a numerical example is given to show the feasibility and effectiveness of the method. the result shows that it is easier than other methods of integrating subjective and objective information
文摘:研究了結合主觀和客觀信息的模糊多屬性決策問題，其中主客觀信息分別由屬性權重的兩兩比較矩陣和決策矩陣組成.提出一種結合主觀和客觀信息的特徵向量決策方法，給出了2種求解基於主客觀特徵向量法的模糊多屬性決策方法.這種方法通過求解2個線性目標規劃模型得到最優屬性權重，然後，通過對決策信息進行簡單的加權集結，得到所有方案的排序結果.最後，通過一個算例說明了該方法的實用性和有效性.結果表明，該方法要比其他主客觀結合多屬性決策方法簡單 -
An integrated approach is proposed to investigate the fuzzy multi - attribute decision - making ( madm ) problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. an eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an madm problem. the simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. finally, a numerical example is given to show the feasibility and effectiveness of the method. the result shows that it is easier than other methods of integrating subjective and objective information
研究了結合主觀和客觀信息的模糊多屬性決策問題，其中主客觀信息分別由屬性權重的兩兩比較矩陣和決策矩陣組成.提出一種結合主觀和客觀信息的特徵向量決策方法，給出了2種求解基於主客觀特徵向量法的模糊多屬性決策方法.這種方法通過求解2個線性目標規劃模型得到最優屬性權重，然後，通過對決策信息進行簡單的加權集結，得到所有方案的排序結果.最後，通過一個算例說明了該方法的實用性和有效性.結果表明，該方法要比其他主客觀結合多屬性決策方法簡單 -
Improved decision matrix and attribute reduction
改進的決策矩陣及其屬性約簡方法 -
An attribute reduction algorithm based on the relation matrix of rough set
基於粗糙集相關矩陣的屬性約簡演算法 -
An algorithm of attribute frequency reduction based on discernibility matrix
基於可辨識矩陣的屬性頻率約簡演算法 -
Under the condition that the lower - layer elements and their dominating upper - layer elements are considered as the condition attributes and the decision attributes separately, the following problems are studied : refining of assessment index system, acquirement of index weight and the constructing of judgment matrix based on the reduction and the attribute importance theory in rough sets, which achieve the sufficiency use of field knowledge for analytical hierarchy process and decision support of the hierarchy problems for rough sets
摘要將層次分析模型中下層因素與支配它的上層因素分別視為條件屬性和決策屬性，藉助粗糙集的約簡和屬性重要性理論，研究了融合粗糙集的層次分析法的指標體系的完善、指標權重的確定、判斷矩陣的構造等問題，實現了層次分析法時領域知識的利用及粗糙集對層次結構問題的決策支持。 -
Using the statistic characterization of data, the relevant knowledge reduction algorithm is put forward by combining the probability with classification rules ; using the characterization of fuzzy attributes, the decision system with subjection degree attribute is built by combing the rough set theory and fuzzy set theory, and the idea of distinguish matrix is induced to the concealed decision system to reduce data
利用數據的統計特徵，將概率測度與分類規則結合起來，提出了相應的知識西北工業大學博士學位論文約減演算法;利用模糊屬性集合的特點，把粗糙集合與模糊集合有機結合起來，將粗糙集中分辨矩陣的思想引入到具有隸屬度屬性的隱式決策系統中進行數據約減。 -
Algorithm for attribute reduction based on attribute significance of binary discernible matrix
基於二進制可辨矩陣屬性重要度的屬性約簡演算法 -
On one hand, we improve on one of the existed algorithms which named attribute reduction algorithm based on discernility matrix and logic operation. we propose a new transformation method from conjunction matrix to disjunction matrix that avoids the manual work or global search and can save the time and space. on the other hand, most traditional methods didn ’ t integrate with database operations
主要做了兩方面的工作，一方面，對已有的基於可辨識矩陣和邏輯運算的屬性約簡演算法進行了改進，提出了一種從合取項矩陣到析取項矩陣直接轉化的方法，避免了傳統的人工轉化或全局搜索的方法，節省了空間和時間。 -
The attribute reduction of matrix algorithm based on rough set theory
基於粗糙集的屬性約簡的矩陣方法 -
A complete algorithm for attribute reduction based on discernibility matrix
一種基於差別矩陣的屬性約簡完備演算法 -
A new method of attribute reduction of decision table based on discernibility matrix
一種新的基於區別矩陣的決策表屬性約簡方法 -
From the mapping relationship between information vector matrix and relative vectors, rough approximation, attribute relative reductions and selecting optimal attribute reductions set algorithms based on binary vector matrix were proposed
摘要根據向量矩陣與向量之間的映射關系，研究了基於二元向量矩陣演算法的粗糙近似、屬性約簡以及最優屬性約簡集的獲取。 -
After that we study on the ordered decision table and propose a new heuristic attribute reduction algorithm based on dominance matrix, whose time complexity is polynomial
再次，對有序決策表進行了研究，提出了一種基於優勢矩陣的啟發式屬性約簡演算法。 -
The subjective weight offered by decision - makers and the objective weight calculated by decision - matrix are sampled for any decision attribute, which are calculated through programming methods in order to make the decision results reliable and credible
對每個決策屬性，將各個決策者給出的主觀權重和客觀權重作為樣本點，採用規劃的方法來集成主觀權重和客觀權重，使決策結果更加可靠、可信。 -
After a brief description of concepts involved in the paper, such as rough set theory and the indiscernibility relation, the methods of how to preprocess the loss value of data and how to discrete the data are discussed. the algorithms of attribute < wp = 6 > reduction and value reduction in rough set theory are researched in depth, and then the ordinary reduction algorithms are given. the improved algorithms based on discernibility matrix and decision matrix are put forward
論文在對所涉及的粗糙集理論以及不可分辨關系等概念進行了簡要的闡述后，接著對數據缺失值如何進行預處理以及如何進行數據的離散化處理等方法進行了探討，然後展開了對粗糙集理論中屬性約簡以及值約簡等演算法更進一步的研究，給出了常規約簡演算法，並在此基礎上提出了基於可辨識矩陣以及決策矩陣的改進演算法，結果表明演算法具有更高的約簡效果。 -
This paper shows three aspects as follow : 1. an algorithm of attribute reduction based on discernibility matrix - - - - ardm is presented. through analyzing to the algorithm of attribute reduction based on discernibility matrix, the facts that affect time efficiency are found, and the absorptivity in the proposition calculation is used to the process of constructing the discernibility matrix, then the effectless repeated elements are deleted, accordingly the efficiency of attribute reduction is improved
本文的主要研究成果有以下三個方面： 1 .提出了一種基於區分矩陣的屬性約簡演算法ardm通過對基於區分矩陣的屬性約簡演算法進行分析，找出影響時間效率的因素並將命題演算中的吸收率用於構造區分矩陣的過程中，從而去掉了在區分函數中不起作用的「重復」元素，提高了屬性約簡的效率。 -
And then, an improved attributes reduction algorithm is given based on the information quantity of single attribute and the discernibility matrix
該演算法是基於信息量的概念，利用單屬性條件信息量進行屬性約簡，並用可辨識矩陣進行修正。 -
Examples of the two aspects of three representative heuristic algorithms are given through structured methods respectively. a new attribute reduction algorithm based on discernibility matrix is introduced in this paper, which need not the step to get rid of redundant attributes and can avoid the influence of unimportant attributes and the interference between attributes and is tested through expriments
在更充分的挖掘分明矩陣中信息的基礎上提出一種新的基於分明矩陣的啟發式屬性約簡演算法，不需要消除冗餘屬性的步驟，並且可以克服屬性受到不重要屬性的千擾和屬性間的相互干擾，通過實驗驗證了此演算法。
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