基于知识量加权的直觉模糊均值聚类方法  

Weighted knowledge amount-based intuitionistic fuzzy C-means method

作　　者：郭凯红[1] 吴峥 李冬 Guo Kaihong;Wu Zheng;Li Dong(School of Information,Liaoning University,Shenyang 110036,China)

机构地区：[1]辽宁大学信息学院,沈阳110036

出　　处：《计算机应用研究》2023年第4期1088-1094,共7页Application Research of Computers

基　　金：国家自然科学基金资助项目(71771110);辽宁省教育厅科学研究项目(LJKZ0094)。

摘　　要：针对聚类算法中特征数据对聚类中心贡献的差异性及算法对初始聚类中心的敏感性等问题,提出一种基于知识量加权的直觉模糊均值聚类方法。首先将原始数据集直觉模糊化并改进最新的直觉模糊知识测度计算知识量,据此实现数据集特征加权,再利用核空间密度与核距离初始化聚类中心,以提高高维特征数据集的计算精度与聚类效率,最后基于类间样本距离与最小知识量原理建立聚类优化模型,得到最优迭代算法。基于UCI人工数据集的实验结果表明,所提方法较大程度地提高了聚类的准确性与迭代效率,分类正确率及执行效率分别平均提高了10.63%和31.75%,且具有良好的普适性和稳定性。该方法首次将知识测度新理论引入模糊聚类并取得优良效果,为该理论在其他相关领域的潜在应用开创了新例。Aiming at the differences in the contribution of feature data to the cluster centers in the clustering algorithm and the sensitivity of the algorithm to the initial cluster centers,this paper proposed a weighted knowledge amount-based intuitionistic fuzzy C-means method(WKAIFCM).Firstly,this method fuzzed the original dataset intuitionistically and improved the latest intuitionistic fuzzy knowledge measure to calculate the knowledge amount which utilized in the feature weighting of dataset.Secondly,this method initialized the cluster centers to improve the calculation accuracy and clustering efficiency of high-dimensional feature dataset by kernel space density and kernel distance.Finally,based on the principle of sample distance between clusters and the principle of minimum knowledge amount,this method established a clustering optimization model to get the optimal iterative algorithm.The experimental results based on the UCI artificial dataset show that the proposed method can greatly improve the accuracy and iterative efficiency of clustering.The classification accuracy and execution efficiency are increased by 10.63%and 31.75%respectively,and this method has good universality and stability.This paper introduces a new theory of knowledge measure into fuzzy clustering for the first time and gets extraordinary results,which creates a new case for the potential application of this theory in other related fields.

关 键 词：知识测度 直觉模糊均值聚类算法 数据加权 聚类中心初始化 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]