Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

Data processing of lie detector based on fuzzy clustering analysis

Authors
Zilong Chen, Junru Wang, Zhiwei Gong, Quanbo Liu
Corresponding Author
Zilong Chen
Available Online May 2015.
DOI
10.2991/asei-15.2015.332How to use a DOI?
Keywords
Data Processing, Fuzzy Clustering, Psychological lie-detection.
Abstract

In this paper, we analyze the problem of many data processing in psychological-detection, then, we deal with the problem based on Fuzzy Clustering, Fuzzy Clustering can use less variable to replace previous variable while the quantity of information is invariant, so, we can eliminate redundancy of information. Last, we did an experiment by our homemade lie detector, then we analyze the data based on Fuzzy Clustering, we found that the previous 6 parameters can be replaced by 4 new parameters, and the information almost didn’t lose, so Fuzzy Clustering can be a good choice for data processing.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
10.2991/asei-15.2015.332
ISSN
2352-5401
DOI
10.2991/asei-15.2015.332How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zilong Chen
AU  - Junru Wang
AU  - Zhiwei Gong
AU  - Quanbo Liu
PY  - 2015/05
DA  - 2015/05
TI  - Data processing of lie detector based on fuzzy clustering analysis
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 1683
EP  - 1686
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.332
DO  - 10.2991/asei-15.2015.332
ID  - Chen2015/05
ER  -