additive attributes 中文意思是什麼
additive attributes
解釋
增添屬性- additive : adj. 1. 附加的，增加的。2. 【化學】加成的，加和的。3. 【數學】加法的；加性的。n. 1. 添加劑；添加物。2. 【數學】加法。
- attributes : 屬性特徵
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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 -
First, the thesis introduces the definitions and the attributes of the higher - order statistics. it is insensitive to additive gaussian noise ( white or colored ), which is what we base on to doa problems. then two doa estimation algorithms based on higher - order statistics are presented, one is that forming cumulant matrix pencil used in esprit to estimate doa problems, the other is spectrum estimation method for doa estimation based on the eigenstructure analysis of the fourth - order cumulant, and comparing the effects of the estimation to conventional covariance - based doa algorithms "
論文首先對高階統計量的定義和性質作了介紹，特別指出了高階統計量對加性高斯噪聲（白色或有色）不敏感，這是我們利用它進行波達方向估計的理論依據，然後文中提出了兩種基於高階統計量的波達方向估計方法，一種是利用子空間旋轉不變技術構造四階累積量矩陣進行估計的方法，另一種是基於四階累積量陣特徵分解的空間譜估計測向方法，並將它們的估計效果與傳統協方差方法的效果進行比較。
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