• 人工智能 •

### 基于密度调整和流形距离的近邻传播算法

1. 合肥工业大学管理学院 合肥230009;合肥工业大学过程优化与智能决策教育部重点实验室 合肥230009,合肥工业大学管理学院 合肥230009;合肥工业大学过程优化与智能决策教育部重点实验室 合肥230009,合肥工业大学管理学院 合肥230009;合肥工业大学过程优化与智能决策教育部重点实验室 合肥230009,北京航空航天大学自动化科学与电气工程学院 北京100191
• 出版日期:2018-12-01 发布日期:2018-12-01
• 基金资助:
本文受国家“863”云制造主题项目(2015AA042101),国家自然科学基金重大研究计划培育项目(91546108),国家自然科学基金项目(71271071,71301041)资助

### Affinity Propagation Clustering Algorithm Based on Density Adjustment and Manifold Distance

XIA Chun-meng, NI Zhi-wei, NI Li-ping and ZHANG Lin

• Online:2018-12-01 Published:2018-12-01

Abstract: As affinity propagation(AP)clustering is sensitive to the dataset with scaling parameter and various form while calculating the similarity matrix and the cluster result is not ideal,an affinity propagation clustering algorithm based on density adjustment and manifold distance was proposed.The algorithm introduces local density of data and manifold theory into affinity propagation clustering,and uses a way of distance measure based on manifold structure and density adjustment to describe the clusters’ actual structure better,making up the similarity matrix’s deficiency.At the same time,the algorithm is more efficient.Simulation experiment was done on artificial datasets and standard datasets.The result shows the effectiveness and superiority of proposed algorithm.

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