期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
故障案例的聚类检索及相关性评估方法研究 被引量:2
1
作者 柳玉 贲可荣 《计算机科学与探索》 CSCD 2012年第6期545-556,共12页
针对传统最近邻(nearest neighbor,NN)方法仅适用于精确特征属性、时间开销与历史案例数量成正比、检出案例与目标不相关等问题,提出了一种故障案例的聚类检索方法;建立了五种故障特征之间的相似度计算模型,引入区间作为不确定数值特征... 针对传统最近邻(nearest neighbor,NN)方法仅适用于精确特征属性、时间开销与历史案例数量成正比、检出案例与目标不相关等问题,提出了一种故障案例的聚类检索方法;建立了五种故障特征之间的相似度计算模型,引入区间作为不确定数值特征的表示手段,构建了案例之间的灰色关联相似度模型;运用聚合分析启发案例索引的创建,据此改进了NN检索过程,并且使用等级相关对齐度量来评估检出案例的相关性。最后通过一个实例阐述了方法的可行性,以及两组实验验证了方法的性能优势。 展开更多
关键词 案例推理 灰色关联相似度 聚类 最近邻 案例对齐
下载PDF
MULTIVARIATE ABSOLUTE DEGREE OF GREY INCIDENCE BASED ON DISTRIBUTION CHARACTERISTICS OF POINTS
2
作者 张可 王岩 +1 位作者 辛江慧 许叶军 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2012年第2期145-151,共7页
The analysis result of absolute degree of grey incidence for multivariate time series is often inconsistent with the qualitative analysis. To overcome this shortage, a multivariate absolute degree of grey incidence ba... The analysis result of absolute degree of grey incidence for multivariate time series is often inconsistent with the qualitative analysis. To overcome this shortage, a multivariate absolute degree of grey incidence based on distribution characteristics of points is proposed. Based on the geometric description of multivariate time se- ries, the neighborhood extrema are extracted in the different regions, and a characteristic point set is constructed. Then according to the distribution of the characteristic point set, a characteristic point sequence reflecting the ge- ometric features of multivariate time series is obtained. The incidence analysis between multivariate time series is transformed into the relational analysis between characteristic point sequences, and a grey incidence model is established. The model possesses the properties of translational invariance, transpose and rank transform invari- ance, and satisfies the grey incidence analysis axioms. Finally, two cases are studied and the results prove the ef- fectiveness of the model. 展开更多
关键词 grey system absolute degree of grey incidences multivariate time series similarity measure
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部