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Dynamic Maintenance of Rough Fuzzy Approximations with the Variation of Objects and Attributes

  • Yanyong Huang
  • Tianrui Li
  • Shi-jinn Horng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9437)

Abstract

In many fields including medical research, e-business and road transportation, data may vary over time, i.e., new objects and new attributes are added. In this paper, we present a method for dynamically updating approximations based on rough fuzzy sets under the variation of objects and attributes simultaneously in fuzzy decision systems. Firstly, a matrix-based approach is proposed to construct the rough fuzzy approximations on the basis of relation matrix. Then the method for incrementally computing approximations is presented, which involves the partition of the relation matrix and partly changes its element values based the prior matrices’ information. Finally, an illustrative example is employed to validate the effectiveness of the proposed method.

Keywords

Fuzzy decision system Rough fuzzy set Incremental learning Matrix 

Notes

Acknowledgements

This work is supported by the National Science Foundation of China (No. 61175047), NSAF (No. U1230117) and the Young Software Innovation Foundation of Sichuan Province, China (No. 2014-046).

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Authors and Affiliations

  1. 1.School of Information Science and TechnologySouthwest Jiaotong UniversityChengduChina
  2. 2.Tianfu Institute of MathematicsTianfu College of Southwestern University of Finance and EconomicsChengduChina

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