cluster analysis is argued to process based on weighted distance coefficient and system similarity methods to enhance the validity of the clustering result 提出以加權(quán)距離和系統(tǒng)相似度量方法為基礎(chǔ)進(jìn)行聚類分析,提高聚類結(jié)果的有效性。
classification and decision-making function is established to solve the product instance . the minimum weighted distance classifier and the maximum system similarity classifier is designed to enhance the precision of classification . the minimum risk decision-making based on system similarity is founded to minimize the loss brought by decision-making 針對(duì)機(jī)械產(chǎn)品實(shí)例建立分類決策函數(shù),設(shè)計(jì)了最小加權(quán)距離分類器和最大系統(tǒng)相似度分類器,在保證適用范圍的前提下提高分類的精度,并提出基于系統(tǒng)相似度的最小風(fēng)險(xiǎn)決策,確保決策帶來的損失最小。
classification and decision-making function is established to solve the product instance . the minimum weighted distance classifier and the maximum system similarity classifier is designed to enhance the precision of classification . the minimum risk decision-making based on system similarity is founded to minimize the loss brought by decision-making 針對(duì)機(jī)械產(chǎn)品實(shí)例建立分類決策函數(shù),設(shè)計(jì)了最小加權(quán)距離分類器和最大系統(tǒng)相似度分類器,在保證適用范圍的前提下提高分類的精度,并提出基于系統(tǒng)相似度的最小風(fēng)險(xiǎn)決策,確保決策帶來的損失最小。
after the weightiness of product attributes being researched, a new method is established to calculate the weight of attributes . the method is applied in weighted distance coefficient and system similarity to measure similarity degree . it enhances the objectivity and accuracy of the similarity measures 探討了在相似度量中機(jī)械產(chǎn)品系統(tǒng)特征屬性的重要性問題,提出一種新的權(quán)重值確定方法,在此基礎(chǔ)上建立加權(quán)距離系數(shù)法,并研究了系統(tǒng)相似度量方法,提高了相似度量的客觀性與準(zhǔn)確性。