Application of hierarchical cluster analysis in raising outlay of science research 聚類分析在我國科研經(jīng)費籌集中的應(yīng)用
Hierarchical clustering method 系統(tǒng)聚類法
Hierarchical cluster analysis and comprehensive evaluation of zizania caduciflora germplasm 茭白資源的系統(tǒng)聚類分析及綜合評估
A hierarchical clustering algorithm and cooperation analysis for wireless sensor networks 無線傳感器網(wǎng)絡(luò)中一種層次分簇算法及協(xié)作性分析
Expected results were achieved in the hierarchical clusters of the chromatographic data of the plants of ephedrine which supplied the foundation for studying crude drugs category 色譜數(shù)據(jù)的系統(tǒng)聚類結(jié)果得到了預(yù)期效果,為研究麻黃屬藥材的類別提供了依據(jù)。
At first , the data surface is partitioned into small blocks , and points in each block are reorganized into error - controlled lods by hierarchical clustering and lod organization 首先對輸入模型進行分塊處理,獲取的每一分塊分別建立誤差控制下的多分辨率數(shù)據(jù)結(jié)構(gòu)。
After 30 provinces aging are hierarchical clustered , 5 models are got : high aging , middle - high aging , middle aging , light - middle aging , slight aging 可將老齡化分為五種模式:高度老齡化模式、中高度老齡化模式、中度老齡化模式、中低度老齡化模式、低度老齡化模式。
Through some specific experiments , we analyse and compare the characters of some discretization methods such as hierarchical clustering analysis , recursive minimal entropy method , and one - rule 通過具體實驗,分析和比較了層次聚類法、遞歸最小熵法和one - rule等離散化方法的性能特點。
In the field of clustering , by comparing some clustering methods and analysing characteristic of science data , we propose an improved hierarchical clustering method synthetic idea of k - means method 在聚類方面,經(jīng)過比較各種聚類算法和分析科學(xué)數(shù)據(jù)的特點,提出了結(jié)合k -平均思想的改進型系統(tǒng)聚類算法。
In contrast to most existing fuzzy identification methods , this method uses a hierarchical clustering architecture based on a hybrid neural network for decreasing computational cost of fuzzy identification procedures 與現(xiàn)有方法不同,該模糊辨識方法采用自組織神經(jīng)網(wǎng)絡(luò)和模糊聚類網(wǎng)絡(luò)兩部分組成的三層神經(jīng)網(wǎng)絡(luò)來實現(xiàn)。