Fuzzy statistic clustering theory may be applied to establish a subject function taking safety degree of banks as a clustering criterion to classify for quantitative analysis , and shishou river is taken for an instance 摘要為定量分析岸坡發(fā)生崩岸的危險(xiǎn)程度,采用模糊統(tǒng)計(jì)聚類理論,建立了以岸坡安全程度為聚類標(biāo)準(zhǔn)的隸屬函數(shù),并以石首河段為例對(duì)岸坡進(jìn)行了聚類判別。
Conventional clustering criteria - based algorithms is a kind of local search method by using iterative mountain climbing technique to find optimization solution , which has two severe defects - sensitive to initial data and easy as can get into local minimum 傳統(tǒng)的基于聚類準(zhǔn)則的聚類算法本質(zhì)上是一種局部搜索算法,它們采用了一種迭代的爬山技術(shù)來尋找最優(yōu)解,存在著對(duì)初始化敏感和容易陷入局部極小的致命缺點(diǎn)。
Most existing clustering algorithms are classified and inter - compared from three different viewpoints , namely clustering criteria , cluster representation , and algorithm framework , and analysed and evaluated with hybrid methods , incremental algorithms , automation and visualization 從聚類準(zhǔn)則、聚類的表示、算法框架等不同角度來考察并區(qū)分這些算法,然后從混合聚類方法、增量聚類、自動(dòng)化和可視化等技術(shù)方面對(duì)現(xiàn)有算法加以比較分析評(píng)價(jià)。