A comprehensive survey of clustering algorithms
Data analysis is used as a common method in modern science research, which is across
communication science, computer science and biology science. Clustering, as the basic …
communication science, computer science and biology science. Clustering, as the basic …
BIRCH: an efficient data clustering method for very large databases
T Zhang, R Ramakrishnan, M Livny - ACM sigmod record, 1996 - dl.acm.org
Finding useful patterns in large datasets has attracted considerable interest recently, and
one of the most widely studied problems in this area is the identification of clusters, or …
one of the most widely studied problems in this area is the identification of clusters, or …
Clustering algorithms research
孙吉贵， 刘杰， 赵连宇 - Journal of software, 2008 - jos.org.cn
对近年来聚类算法的研究现状与新进展进行归纳总结. 一方面对近年来提出的较有代表性的聚类
算法, 从算法思想, 关键技术和优缺点等方面进行分析概括; 另一方面选择一些典型的聚类算法和 …
算法, 从算法思想, 关键技术和优缺点等方面进行分析概括; 另一方面选择一些典型的聚类算法和 …
A comprehensive review of the latest path planning developments for multi-robot formation systems
There has been a continuous interest in multi-robot formation systems in the last few years
due to several significant advantages such as robustness, scalability, and efficiency …
due to several significant advantages such as robustness, scalability, and efficiency …
基于最优划分的K-Means 初始聚类中心选取算法
张健沛， 杨悦， 杨静， 张泽宝 - 系统仿真学报, 2009 - cqvip.com
针对传统K-Means 算法聚类过程中, 聚类数目k 值难以准确预设和随机选取初始聚类中心造成聚
类精度及效率降低等问题, 提出一种基于最优划分的K-Means 初始聚类中心选取算法 …
类精度及效率降低等问题, 提出一种基于最优划分的K-Means 初始聚类中心选取算法 …
A fuzzy clustering model for multivariate spatial time series
R Coppi, P D'Urso, P Giordani - Journal of Classification, 2010 - Springer
Clustering of multivariate spatial-time series should consider: 1) the spatial nature of the
objects to be clustered; 2) the characteristics of the feature space, namely the space of …
objects to be clustered; 2) the characteristics of the feature space, namely the space of …
[HTML][HTML] MSGC: Multi-scale grid clustering by fusing analytical granularity and visual cognition for detecting hierarchical spatial patterns
Spatial clustering is a widely used data mining method for discovery of spatial aggregation
pattern. However, existing methods often neglect scale dependence, impeding the full …
pattern. However, existing methods often neglect scale dependence, impeding the full …
[HTML][HTML] A novel fast classification filtering algorithm for LiDAR point clouds based on small grid density clustering
X Deng, G Tang, Q Wang - Geodesy and Geodynamics, 2022 - Elsevier
Clustering filtering is usually a practical method for light detection and ranging (LiDAR) point
clouds filtering according to their characteristic attributes. However, the amount of point …
clouds filtering according to their characteristic attributes. However, the amount of point …
A comparative study of clustering algorithms
In present era, data analysis plays vital role in various domains. Data clustering is a data
analysis technique used for grouping of data objects based on unsupervised learning. Many …
analysis technique used for grouping of data objects based on unsupervised learning. Many …