Computer Science ›› 2014, Vol. 41 ›› Issue (8): 233-240.doi: 10.11896/j.issn.1002-137X.2014.08.050

Previous Articles     Next Articles

Novel Method of Uncertain Data Modeling and Classification Based on Cloud Model

QIN Li and LI Bing   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Data contain inherent uncertainty.Sampling errors,data staling and repeated measurements are all the sources of uncertainty,so the analysis of uncertain data obtains more and more attention in many applications.The value of each traditional uncertain data is represented as domain over which a probability distribution function is defined.Because uncertainty data have fuzziness and randomness,and the traditional probability distribution function is difficult to define the actual distribution of the uncertainty data,this paper proposed a cloud modeling process of uncertainty data by the cloud drops distribution,and also designed a classify method by cloud union and similarity computing of cloud.Cloud model can effectively merge the randomness and fuzziness together,and can analyze uncertain data more effectively.For it’s realistic reflection of actual distribution of the uncertain data,our experiments also prove the validity of this method.

Key words: Uncertain data classification,Gaussian cloud,Uniform cloud,Cloud union,Cloud similarity computing

[1] 王意洁,李小勇,祁亚斐,等.不确定数据查询技术研究[J].计算机研究与发展,2012,9(7):1460-1466
[2] Parag A,Jennifer W.Generalized Uncertain Databases:FirstSteps[C]∥Proceedings of the 4’ International VLDB Workshop on Management of Uncertain Data (MUD 2010) in conjunction with VLDB 2010.Twente,Netherlands:Singapore,2010:99-111
[3] Smith T,Kao Ben,Yip K Y,et al.Decision Trees for Uncertain Data[C]∥Proceedings of the 25th IEEE International Confe-rence on Data Engineering (ICDE 2009).Shanghai,China:IEEE,2009:441-444
[4] Qin Biao,Xia Yu-ni,Li Fang.DTU:A Decision Tree for Uncertain Data[C]∥Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009).Bangkok,Thailand:Springer,2009:4-15
[5] 周帅印,李晨,王勇,等.FDTU:针对不确定数据的快速决策树生成算法[J].计算机研究与发展,2010,7(zl):363-369
[6] Qin Biao,Xia Yu-ni,Sunil P,et al.A Rule-Based Classification Algorithm for Uncertain Data[C]∥Proceedings of the 25th IEEE International Conference on Data Engineering (ICDE 2009).Shanghai,China:IEEE,2009:1633-1640
[7] Qin Biao,Xia Yu-ni,Sunil P,et al.Rule induction for uncertain data[J].Knowledge Information Systems,2011,9(1):103-130
[8] Ren Jiang-tao,Lee S D,Chen Xian-lu,et al.Naive Bayes Classification ofUncertain Data[C]∥Proceedings of the 9th IEEE International Conference on Data Mining (ICDM2009).Miami,USA:IEEE,2009:944-949
[9] Qin Biao,Xia Yu-ni,Wang Shan,et al.A novel Bayesian classification for uncertain data[J].Knowledge-Based Systems,2011,24(8):1151-1158
[10] Chau M,Cheng R,Kao Ben.Uncertain Data Mining:A New Research Direction[C]∥Proceedings of the Workshop on the Sciences of the Artificial.Hualien,Taiwan:2005:89-102
[11] 王国胤,李德毅,等.云模型与粒计算[M].北京:科学出版社,2012:1-39
[12] Liu Yu,Chen Gui-sheng.Cloud Model Based Classifier[C]∥2009 International Conference on Test and Measurement(ICTM2009).HongKong:IEEE,2009:427-430
[13] 张国英,沙芸,余有明,等.基于属性相似度的云分类器[J].北京理工大学学报,2005,5(6):499-503
[14] 刘达,张国英,刘冠洲,等.基于特征筛选的云分类器[J].北京石油化工学院学报,2011,9(1):10-14
[15] 石礼娟,文友先,牟同敏,等.逆向云在垩白识别中的应用[J].农业机械学,2009,0(12):196-199
[16] Shi Li-juan,Wen You-xian,Xie Xin-gang.Classifier Based onCloud Model and Its Application[C]∥Computational Intelligence and Software Engineering.WuHan,China,IEEE,2009:1-4
[17] Lu Hong-fei,Pi Er-xu,Peng Qiu-fa,et al.A particle swarm optimization-aided fuzzy cloud classifier applied for plant numerical taxonomy based on attribute similarity[J].Expert Systems with Applications,2009,6:9388-9397
[18] Pi Er-xu,Lu Hong-fei,Jiang Bo,et al.Precise plant classificationwithin genus level based on simulated annealing aided cloud classifier[J].Expert Systems with Applications,2011,38:3009-3014
[19] Qin Kun,Xu Kai,Liu Fei-long,et al.Image segmentation based on histogram analysis utilizing the cloud model[J].Computers & Mathematics with Applications,2011,62(7):2824-2833
[20] 李德毅,杜鹢.不确定性人工智能[M].北京:国防工业出版社,2005:255-257
[21] 李德毅,刘常昱.论正态云模型的普适性[J].中国工程科学,2004,6(8):28-33
[22] 李德毅,孟海军,史雪梅.隶属云和隶属云发生器[J].计算机研究与发展,1995,2(6):16-21
[23] 扬朝辉,李德毅.二维云模型及其在预测中的应用[J].计算机学报,1998,1(11):962-968
[24] 刘禹,李德毅,张光卫,等.云模型雾化特性及在进化算法中的应用[J].电子学报,2009,37(8):1651-1658
[25] 刘禹,李德毅.正态云模型雾化性质统计分析[J].北京航空航天大学学报,2010,6(11):1320-1324
[26] 罗自强,张光卫,李德毅.一维正态云的概率统计分析[J].信息与控制,2007,6(4):471-475
[27] 吕辉军,王晔,李德毅,等.逆向云在定性评价中的应用[J].计算机学报,2003,6(8):1009-1014
[28] 刘常昱,冯芒,戴晓军,等.基于云X信息的逆向云新算法[J].系统仿真学报,2004,6(11):2417-2420
[29] 邸凯昌,李德毅,李德仁.云理论及其在空间数据发掘和知识发现中的应用[J].中国图象图形学报,1999,4(11):930-935
[30] 蒋嵘,李德毅,范建华.数值型数据的泛概念树的自动生成方法[J].计算机学报,2000,23(5):470-476
[31] 秦昆,李德毅,许凯.基于云模型的图像分割方法研究[J].测绘信息与工程,2006,1(5):3-5

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!