The Rationality Inspection Global Method of Measuring Data

DOI

10.2991/iccsae-15.2016.133How to use a DOI?

Keywords

Rationality inspection; least square; global method; accumulated error

Abstract

Least square method for polynomial extrapolation is one of data rationality inspection methods that are often used to identify outliers. However, the method is local and only inspects the rationality of current data points. If the outliers are accepted before, the method can cause the following normal points to be abandoned and the abnormal points to be received, which will lead to the accumulation of errors. Moreover, because of the method needs to accumulate points before inspection, the initial data points cannot be inspected. To this end, this paper presents a global data nationality inspection algorithm. The method is fast and accurate, and can effectively eliminate the accumulated error in global.

Copyright

© 2016, 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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TY  - CONF
AU  - Zhao Liu
AU  - Maodong Pan
AU  - Shaolin Wang
AU  - Jiangtao Wei
PY  - 2016/02
DA  - 2016/02
TI  - The Rationality Inspection Global Method of Measuring Data
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 715
EP  - 718
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.133
DO  - 10.2991/iccsae-15.2016.133
ID  - Liu2016/02
ER  -