Journal of Systems Engineering and Electronics 2010, 21(1) 142-147 DOI:   10.3969/j.issn.1004-4132.2010.01.023  ISSN: 1004-4132 CN: 11-3018/N

Current Issue | Archive | Search                                                            [Print]   [Close]
Information and Service
This Article
Supporting info
Service and feedback
Email this article to a colleague
Add to Bookshelf
Add to Citation Manager
Cite This Article
Email Alert
missing value
K-means with soft constraints clustering
missing value insensitive kernel

Modelling method with missing values based on clustering and support vector regression

Ling Wang∗, Dongmei Fu, Qing Li, and Zhichun Mu

Information Engineering School, University of Science and Technology Beijing, Beijing 100083, P. R. China


Most real application processes belong to a complex nonlinear system with incomplete information. It is difficult to
estimate a model by assuming that the data set is governed by a global model. Moreover, in real processes, the available data set is usually obtained with missing values. To overcome the shortcomings of global modeling and missing data values, a new modeling method is proposed. Firstly, an incomplete data set with missing values is partitioned into several clusters by a K-means with soft constraints (KSC) algorithm, which incorporates soft constraints to enable clustering with missing values. Then a local model based on each group is developed by using SVR algorithm, which adopts a missing value insensitive (MVI) kernel to investigate the missing value estimation problem. For each local model, its valid area is gotten as well. Simulation results prove the effectiveness of the current local model and the estimation algorithm.

Keywords�� modeling   missing value   K-means with soft constraints clustering   missing value insensitive kernel  
Received  Revised  Online:  
DOI: 10.3969/j.issn.1004-4132.2010.01.023

This work was supported by Key Discipline Construction Program of Beijing Municipal Commission of Education (XK10008043).

Corresponding Authors:
About author:

Similar articles
1��Wang Li & Wang Mingzhe.Modeling of cognitive framework in time-stressed decision making[J]. Journal of Systems Engineering and Electronics, 2009,20(5): 992-1000
2��Wang Huadong, Bao Jingfu & Wu Zhengde.Multislice behavioral modeling based on envelope domain for power amplifiers[J]. Journal of Systems Engineering and Electronics, 2009,20(2): 274-277
3��Fan Ping & Jing Zhanrong.Parametric estimation of ultra wideband radar targets[J]. Journal of Systems Engineering and Electronics, 2009,20(3): 499-503
4��Yin Yongfeng, Liu Bin, Zhong Deming & Jiang Tongmin.On modeling approach for embedded real-time software simulation testing[J]. Journal of Systems Engineering and Electronics, 2009,20(2): 420-426
5��Yanwei Zhao, Ping Zhou, Xiangyang Zhang, and Min Zhang.Application of improved equivalent edge currents in synthetic aperture radar imaging[J]. Journal of Systems Engineering and Electronics, 2010,21(4): 566-571
6��Li Chunlin, Feng Meilai & Li Layuan.Multiple QoS modeling and algorithm in computational grid[J]. Journal of Systems Engineering and Electronics, 2007,18(2): 412-417
7��Qingchao Dong, Zhixue Wang, Weixing Zhu, and Hongyue He.Capability requirements modeling and verification based on fuzzy ontology[J]. Journal of Systems Engineering and Electronics, 2012,23(1): 78-87
8��Tingyu Lin, Xudong Chai, and Bohu Li.Top-level modeling theory of multi-discipline virtual prototype[J]. Journal of Systems Engineering and Electronics, 2012,23(3): 425-437

Copyright by Journal of Systems Engineering and Electronics