计算机应用研究2018，Vol.35Issue(2)：362-366,5.DOI:10.3969/j.issn.1001-3695.2018.02.010
基于粒计算的多尺度聚类尺度上推算法
Upscale algorithm of multi-scale clustering based on granular computing
摘要
Abstract
Research of multi-scale scientific mainly focuses on space or image data in the field of data mining,while paying less attention to multi-scale features of general data.Traditional clustering algorithms are implemented based on single scale,which are not able to discover potential knowledge in data.This paper carried out a study of methods on universal multi-scale clustering with the introduction of granular computing,for the purpose of multilayer and multi-angle of data analysis and single-mining-multiple-using.First of all,this paper described knowledge related to granular computing.Then,it proposed an algorithm called UAMC,with clusters as granularity and clustering centers as feature of granularity to scale conversion,obtaining knowledge of large scale based on mosaic upscaling scheme,for fear of resource waste due to secondly mining.At last,experimental results on datasets from UCI and H province indicate that UAMC algorithm outperforms benchmark algorithms such as K-means in accuracy.Meanwhile,UAMC algorithm is verified to be effective and feasible through the experiments.关键词
多尺度/粒计算/信息粒度/斑块模型/多尺度聚类Key words
multi-scale/granular computing/information granularity/mosaic upscaling scheme/multi-scale clustering分类
信息技术与安全科学引用本文复制引用
赵骏鹏,赵书良,李超,高琳,池云仙..基于粒计算的多尺度聚类尺度上推算法[J].计算机应用研究,2018,35(2):362-366,5.基金项目
国家自然科学基金资助项目(71271067) （71271067）
国家社科基金重大项目(13&ZD091) （13&ZD091）
河北省高等学校科学技术研究项目(QN2014196) （QN2014196）
河北师范大学硕士基金资助项目(xj2015003) （xj2015003）
