An Outlier Fuzzy Detection Method Using Fuzzy Set Theory - IEEE Xplore
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May 2, 2019 · Our key idea is to use fuzzy constraint technology to prune irrelevant objects for outlier detection, during which the nearness measure theory ...
Our key idea is to use fuzzy constraint technology to prune irrelevant objects for outlier detection, during which the nearness measure theory in fuzzy ...
May 17, 2019 · Our key idea is to use fuzzy constraint technology to prune irrelevant objects for outlier detection, during which the nearness measure theory ...
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The key idea is to use fuzzy constraint technology to prune irrelevant objects for outlier detection, during which the nearness measure theory in fuzzy ...
Numerous methods have been created to identify outliers but only on numerical data. Those methods cannot be applied directly to categorical data. So the fuzzy ...
The paper presents a method based on a fuzzy inference system that is capable of pointing out outliers in a series of data. The proposed algorithm has been ...
Jul 18, 2022 · Therefore, in this study we present a method based on the use of the fuzzy three-sigma rule to detect outliers. The novelty of the described ...
Fuzzy set theory by. Zadeh[10] who reveals uncertainity, which belongs to a membership function, Fuzzy partitioning and Applications. Page 2. Outlier Detection ...
In Section 5, an algorithm is proposed for the detection of outliers based on the basic model of rough sets, emphasizing specific aspects of its implementation.
Nov 1, 2011 · Time series analysis is often associated with the discovery of patterns and prediction of features. Forecasting accuracy can be improved by ...