In order to reduce the disadvantageous influence of decision profiles ' scattering on fusion recognition , the decision profile is taken as target ' s feature vector and k - nearest neighbor method is applied to classify the target 為減少目標(biāo)決策分布圖散布對融合識別效果的影響,提出采用k近鄰方法對目標(biāo)的決策分布圖進(jìn)行分類,以實(shí)現(xiàn)融合識別。
Then , because of the characteristic of complex engineering systems like fighters , such as modeling difficulty , multiplicity work situations , difficulty and expensiveness for test , a new kind of fast fault predictor is designed based on an improved k - nearest neighbor method , which neither need math model of system nor need data for train and knowledge 其次,針對殲擊機(jī)等復(fù)雜工程系統(tǒng)建模困難、工作情況多樣、試驗困難且代價高昂的特點(diǎn),提出了一種改進(jìn)k近鄰密度估計方法,設(shè)計了一種完全既不需要系統(tǒng)數(shù)學(xué)模型也不需要故障訓(xùn)練數(shù)據(jù)和先驗知識的實(shí)時故障預(yù)報器。