基于疯狂捕猎秃鹰算法的K均值互补迭代聚类优化
黄鹤,温夏露,杨澜,王会峰,高涛,茹锋

K-means complementary iterative clustering optimization based on crazy-hunting bald eagle search algorithm
He HUANG,Xia-lu WEN,Lan YANG,Hui-feng WANG,Tao GAO,Feng RU
表 1 功能测试函数
Tab.1 Functional test functions
函数 表达式 取值范围
Sphere $ f(x) = \displaystyle \sum\nolimits_{i = 1}^n {x_i^2} $ [−100,100]n
Schwefel 2.22 $ f(x) = \displaystyle \sum\nolimits_{i = 1}^n {\left| {{x_i}} \right|} +\prod\nolimits_{i = 1}^n {\left| {{x_i}} \right|} $ ${ {{[ - 10,10]} }^{{n} } }$
Schwefel 1.2 $ f(x) = {\displaystyle \sum\nolimits_{i = 1}^n {\left( {\displaystyle \sum\nolimits_{j = 1}^i {{x_j}} } \right)} ^2} $ [−100,100]n
Rastrigin $f(x) = \displaystyle \sum\nolimits_{i = 1}^{{n} } { { {\left( {x_i^2 - 10\cos \,\, \left( {2\text{π} {x_i} } \right)+10} \right)}^2} }$ [−5.12,5.12]n
Ackley $\begin{gathered} f(x) = - 20\exp \,\, \left( { - 0.2\sqrt {\dfrac{1}{n}\displaystyle \sum\nolimits_{i = 1}^n {x_i^2} } } \right) - \\\exp \,\, \left( {\dfrac{1}{n}\displaystyle \sum\nolimits_{i = 1}^n {\cos \,\, 2\text{π} {x_i} } } \right)+20+{\rm{e}} \end{gathered}$ [−32,32]n
Griewank $\begin{gathered} f(x) = \dfrac{1}{ {4\;000} }\displaystyle \sum\nolimits_{i = 1}^n { {\left( { {x_i} - 100} \right)}^2} - \\\prod\nolimits_{i = 1}^n {\cos \,\, \left( {\dfrac{ { {x_i} - 100} }{ {\sqrt i } } } \right)} +1 \end{gathered}$ ${ { {[ - 600,600]} }^{{n} } }$