中国机械工程Issue(10)：1381-1386,1387,7.DOI:10.3969/j.issn.1004-132X.2014.10.020
改进的FCM聚类法及其在行驶工况构建中的应用
An Improved FCM Clustering Algorithm and Its Applications of Vehicle Driving Cycle Construction
摘要
Abstract
Since FCM clustering was relatively sensitive to the initial clustering center,iteration was inclined to fall into local extremum and the global optimum was difficult to obtain,a modified FCM method was presented to overcome the above defects.In order to get closer to the global optimal clustering,the data of the principal components were classified by a SOM network,and the obtained weights were used as the initial clustering center of the FCM clustering.The modified FCM clustering method was used for establishing driving cycle in Hefei city.The theoretical analysis and its corre-sponding results indicate that this method possesses a sound precison for establishing driving condi-tions,which can reflect the realistic urban traffic conditions comprehensively.关键词
模糊C均值聚类/自组织映射/主成分分析/行驶工况Key words
fuzzy C means(FCM)clustering/self-organizing maps(SOM)/principal component a-nalysis/driving cycle分类
交通工程引用本文复制引用
石琴,马洪龙,丁建勋,龙建成,凌翔..改进的FCM聚类法及其在行驶工况构建中的应用[J].中国机械工程,2014,(10):1381-1386,1387,7.基金项目
国家自然科学基金资助项目(71071044,71001001,71201041,71271075) （71071044,71001001,71201041,71271075）
高等学校博士学科点专项科研基金资助项目(20110111120023,20120111120022) （20110111120023,20120111120022）
