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利用人工蜂群算法进行地震属性聚类分析

Keywords: 地震属性聚类,人工蜂群算法,串珠状强反射特征,片状弱反射特征,局部最优,最优聚类中心

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Abstract:

？将具有全局搜索能力的人工蜂群算法引入到地震属性聚类中,在人工蜂群算法中蜜蜂被分为引领蜂、跟随蜂和侦察蜂三种,引领蜂寻找蜜源,跟随蜂根据引领蜂带回的蜜源信息搜索新蜜源,若某个蜜源被引领蜂或跟随蜂丢弃,则侦察蜂随机搜索新蜜源代替被丢弃的蜜源.其中每个蜜源代表优化问题的一个可能解,蜜源的花蜜量对应于解的质量,用适应值表示.最优解的搜索过程包括初始化和蜜源更新两个过程,通过蜂群分工协作,搜索最佳聚类中心,解决常规k均值聚类算法存在的多解性问题.利用国际上通用uci机器学习数据库中的iris和wine数据集对常规k均值算法和人工蜂群算法进行了测试,结果表明:基于人工蜂群算法的聚类方法的分类正确率明显高于k均值方法.实际地震数据的聚类结果表明:基于人工蜂群算法的地震属性聚类能精细刻画塔北奥陶系碳酸盐岩岩溶储层的相带特征,并且能较好地描述呈片状弱反射特征的储层分布.

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[11]  karabogadandbasturkb.ontheperformanceofartificialbeecolonyalgorithm[j].appliedsoftcomputing.2008,8(1):687-697
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