Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System
Information granule is the basic element in granular computing (GrC), and it can be obtained according to the granulation criterion. In neighborhood rough sets, current uncertainty measures focus on computing the knowledge granulation of single granular space and have two main limitations: (i) negle...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2021-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/9977488 |
id |
doaj-38fa607bddf34dd886c82b94e95b5b5a |
---|---|
record_format |
Article |
spelling |
doaj-38fa607bddf34dd886c82b94e95b5b5a2021-05-31T00:33:31ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/9977488Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood SystemJie Yang0Tian Luo1Fan Zhao2Shuai Li3Wei Zhou4School of Physics and Electronic ScienceSchool of Physics and Electronic ScienceChongqing Key Laboratory of Computational IntelligenceChongqing Key Laboratory of Computational IntelligenceNational Pilot School of SoftwareInformation granule is the basic element in granular computing (GrC), and it can be obtained according to the granulation criterion. In neighborhood rough sets, current uncertainty measures focus on computing the knowledge granulation of single granular space and have two main limitations: (i) neglecting the structural information of boundary regions and (ii) the inability to reflect the difference between neighborhood granular spaces with the same uncertainty for approximating a target concept. Firstly, a fuzziness-based uncertainty measure for neighborhood rough sets is introduced to characterize the structural information of boundary regions. Moreover, from the perspective of distance, based on the idea of density peaks, we present a fuzzy-neighborhood-granule-distance- (FNGD-) based method to discover the relationship between granules in a granular space. Then, to characterize the difference between granular spaces for approximating a target concept, we present the fuzzy neighborhood granular space distance (FNGSD) and fuzzy neighborhood boundary region distance (FNBRD). FNGD, FNGSD, and FNBRD are hierarchically organized from fineness to coarseness according to the semantics of granularity, which provide three-layer perspectives in the neighborhood system.http://dx.doi.org/10.1155/2021/9977488 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jie Yang Tian Luo Fan Zhao Shuai Li Wei Zhou |
spellingShingle |
Jie Yang Tian Luo Fan Zhao Shuai Li Wei Zhou Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System Mathematical Problems in Engineering |
author_facet |
Jie Yang Tian Luo Fan Zhao Shuai Li Wei Zhou |
author_sort |
Jie Yang |
title |
Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System |
title_short |
Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System |
title_full |
Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System |
title_fullStr |
Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System |
title_full_unstemmed |
Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System |
title_sort |
fuzzy knowledge distance with three-layer perspectives in neighborhood system |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1563-5147 |
publishDate |
2021-01-01 |
description |
Information granule is the basic element in granular computing (GrC), and it can be obtained according to the granulation criterion. In neighborhood rough sets, current uncertainty measures focus on computing the knowledge granulation of single granular space and have two main limitations: (i) neglecting the structural information of boundary regions and (ii) the inability to reflect the difference between neighborhood granular spaces with the same uncertainty for approximating a target concept. Firstly, a fuzziness-based uncertainty measure for neighborhood rough sets is introduced to characterize the structural information of boundary regions. Moreover, from the perspective of distance, based on the idea of density peaks, we present a fuzzy-neighborhood-granule-distance- (FNGD-) based method to discover the relationship between granules in a granular space. Then, to characterize the difference between granular spaces for approximating a target concept, we present the fuzzy neighborhood granular space distance (FNGSD) and fuzzy neighborhood boundary region distance (FNBRD). FNGD, FNGSD, and FNBRD are hierarchically organized from fineness to coarseness according to the semantics of granularity, which provide three-layer perspectives in the neighborhood system. |
url |
http://dx.doi.org/10.1155/2021/9977488 |
work_keys_str_mv |
AT jieyang fuzzyknowledgedistancewiththreelayerperspectivesinneighborhoodsystem AT tianluo fuzzyknowledgedistancewiththreelayerperspectivesinneighborhoodsystem AT fanzhao fuzzyknowledgedistancewiththreelayerperspectivesinneighborhoodsystem AT shuaili fuzzyknowledgedistancewiththreelayerperspectivesinneighborhoodsystem AT weizhou fuzzyknowledgedistancewiththreelayerperspectivesinneighborhoodsystem |
_version_ |
1721419690014670848 |