Earticle

초록

영어

A bottle up hyperbox granular computing (HBGrC) is developed based on distance measure. Firstly, hyperbox granule is represented by the beginning point and the end point. Secondly, the distance measure between two hyperbox granules is defined by the beginning points and the end points. Thirdly, operations between two hyperbox granules are designed to the transformation between two hyperbox granule spaces with different granularities, HBGrC is developed by the join operator and the user-defined granularity threshold  on the basis of bottle up scheme. Experimental results shown that HBGrC achieved the better testing accuracies over the machine learning benchmark datasets.

목차

Abstract
 1. Introduction
 2. Motivation and Related Work
  2.1. Motivation
  2.2. Related Work
 3. Hyperbox Granular Computing Based Distance Measure
  3.1. Representation and Granularity for the Hyperbox Granule
  3.2. Distance Measure
  3.3. Operations between Two Hyperbox Granules
  3.4. The Hyperbox Granular Computing Based on Distance Measure
 4. Experiments
  4.1. Classification in 2-dimensional Space
  4.2. Classification in N-dimensional Space
 5. Conclusion
 References

키워드

저자

• Hongbing Liu [ School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China ]
• Huaping Guo [ School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China ]
• Chang-an Wu [ School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605