Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

The Algorithm for Evaluation of Landscape Water Quality based on intuitionistic fuzzy sets of emphasizing hesitancy degree

Authors
HaiFeng Wang, Kun Zhang, Zhuang Li, HongXu Wang
Corresponding Author
HaiFeng Wang
Available Online March 2016.
DOI
https://doi.org/10.2991/icmmct-16.2016.366How to use a DOI?
Keywords
Intuitionistic fuzzy sets; Water quality analysis; Distance; New definition; New formula.
Abstract
Distance measure of intuitionistic fuzzy sets(IFS) is a measure of the difference sizes between two IFS. The original distance measure definition is modified in this paper, the new distance measure definition and a new distance formula of IFS are provided. Pattern recognition method based on distance of intuitionistic fuzzy sets is used for researching on water quality analysis problem. That provides a new way for the study of the same problem. The method is simpler than the current method and the results are in line with the actual.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
https://doi.org/10.2991/icmmct-16.2016.366How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - HaiFeng Wang
AU  - Kun Zhang
AU  - Zhuang Li
AU  - HongXu Wang
PY  - 2016/03
DA  - 2016/03
TI  - The Algorithm for Evaluation of Landscape Water Quality based on intuitionistic fuzzy sets of emphasizing hesitancy degree
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1843
EP  - 1847
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.366
DO  - https://doi.org/10.2991/icmmct-16.2016.366
ID  - Wang2016/03
ER  -