Results 31 to 40 of about 304,299 (338)
A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams
Big Data and Cognitive Computing, 2020 Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data mining and machine learning.
Omar Alghushairy +3 more
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A Sliding Window Variational Outlier-Robust Kalman Filter Based on Student’s t-Noise Modeling
IEEE Transactions on Aerospace and Electronic Systems, 2022 Existing robust state estimation methods are generally unable to distinguish model uncertainties (state outliers) from measurement outliers as they only exploit the current measurement. In this article, the measurements in a sliding window are, therefore,
Fengchi Zhu +4 more
semanticscholar +1 more source
Outlier detection algorithm based on k-nearest neighbors-local outlier factor
Journal of Algorithms & Computational Technology, 2022 The main task of outlier detection is to detect data objects which have a different mechanism from the conventional data set. The existing outlier detection methods are mainly divided into two directions: local outliers and global outliers. Aiming at the
He Xu, Lin Zhang, Peng Li, F. Zhu
semanticscholar +1 more source
Error and anomaly detection for intra-participant time-series data
International Biomechanics, 2017 Identification of errors or anomalous values, collectively considered outliers, assists in exploring data or through removing outliers improves statistical analysis.
David R. Mullineaux, Gareth Irwin
doaj +1 more source
A survey on outlier explanations
The VLDB journal, 2022 While many techniques for outlier detection have been proposed in the literature, the interpretation of detected outliers is often left to users. As a result, it is difficult for users to promptly take appropriate actions concerning the detected outliers.
Egawati Panjei +4 more
semanticscholar +1 more source
On-line detection algorithm of ore grade change in grinding grading system
Open Physics, 2020 In process industry control, process data is critical for both control and fault diagnosis. Timely detection of outliers and mutation point in process data can quickly adjust control parameters or discover potential failures throughout the system. Aiming
Zhao Jianjun, Zhou Junwu
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The efficiency of different outlier detection approaches in geodetic networks: case study for Pobednik statue [PDF]
Geodetski Vestnik, 2018 In the paper the efficacy of two different approaches for outlier detection in geodetic networks is analysed on a test example of a control network for geodetic monitoring of the Pobednik statue in the Kalemegdan Fortress in Belgrade by applying the mean
Mehmed Batilović +5 more
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Progress in Outlier Detection Techniques: A Survey
IEEE Access, 2019 Detecting outliers is a significant problem that has been studied in various research and application areas. Researchers continue to design robust schemes to provide solutions to detect outliers efficiently. In this survey, we present a comprehensive and
Hongzhi Wang, M. Bah, Mohamed Hammad
semanticscholar +1 more source
IEEE Access, 2020 The Received Signal Strength (RSS) fingerprint-based indoor localization method in Wireless Local Area Network (WLAN) environment has been widely used due to its low hardware requirements and high positioning accuracy.
Teng Tan, Lingwen Zhang, Qiumei Li
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Electricity Theft Detection in AMI Based on Clustering and Local Outlier Factor
IEEE Access, 2021 As one of the key components of smart grid, advanced metering infrastructure (AMI) provides an immense number of data, making technologies such as data mining more suitable for electricity theft detection.
Yanlin Peng +6 more
semanticscholar +1 more source