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Published in 2022 at "Journal of Chemometrics"
DOI: 10.1002/cem.3460
Abstract: Assessment of the adequacy of a proposed linear calibration curve is necessarily subjective in chemical analysis. If the outlier points in calibration are not identified and discarded, the constructed model will not have much validity…
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Keywords:
roadmap outlier;
detection univariate;
chemistry;
calibration ... See more keywords
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Published in 2020 at "Research synthesis methods"
DOI: 10.1002/jrsm.1455
Abstract: Network meta-analysis has been gaining prominence as an evidence synthesis method that enables the comprehensive synthesis and simultaneous comparison of multiple treatments. In many network meta-analyses, some of the constituent studies may have markedly different…
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Keywords:
outlier detection;
network meta;
network;
meta analysis ... See more keywords
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Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3876-4
Abstract: Outliers are a critical factor that affects the accuracy of data-based predictions and some other data-based processing; thus, outliers must be effectively detected as soon as possible to improve the credibility of the data. In…
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Keywords:
detection;
minimal weighted;
outlier detection;
data stream ... See more keywords
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Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04421-4
Abstract: Outlier detection has become an important research area in the field of stream data mining due to its vast applications. In the literature, many methods have been proposed, but they work well for simple and…
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Keywords:
large scale;
stream;
outlier detection;
approach large ... See more keywords
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Published in 2021 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-06294-y
Abstract: With the rapid development of internet technology and mobile devices, massive streaming data of spatiotemporal information is available for real-time data mining. Outlier detection is playing as one of the most important analysis tasks for…
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Keywords:
traffic;
outlier detection;
real time;
time urban ... See more keywords
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Published in 2021 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-021-00998-6
Abstract: Outlier detection approaches show their efficacy while extracting unforeseen knowledge in domains such as intrusion detection, e-commerce, and fraudulent transactions. A prominent method like the K-Nearest Neighbor (KNN)-based outlier detection (KNNOD) technique relies on distance…
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Keywords:
detection;
based outlier;
approximate adaptive;
density ... See more keywords
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Published in 2022 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-11671-9
Abstract: Outlier detection is an important research area in the field of machine learning and data science. The presence of outliers in a dataset limits its true usefulness in a real-life scenario. Due to the varied…
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Keywords:
outlier detection;
clustering algorithms;
using ensemble;
detection using ... See more keywords
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Published in 2020 at "Environmental Earth Sciences"
DOI: 10.1007/s12665-020-09197-8
Abstract: The increasing trend on water use for hydraulic fracturing (HF) in multiple plays across the U.S. has raised the need to improve the HF water management model. Such approaches require good-quality datasets, particularly in water-stressed…
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Keywords:
water footprint;
water;
outlier detection;
ford play ... See more keywords
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Published in 2021 at "ISA transactions"
DOI: 10.1016/j.isatra.2021.01.046
Abstract: This paper proposes a novel method for offline outlier detection in nonlinear dynamical systems using an input-output dataset of a Topical Negative Pressure Wound Therapy Device, NPWT. The fundamental characteristics of an NPWT describe a…
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Keywords:
topical negative;
outlier detection;
fuzzy rule;
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Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.02.039
Abstract: A local density-based approach for outlier detection is proposed.The theoretical properties of the proposed outlierness score are derived.Three types of nearest neighbors are presented. This paper presents a simple and effective density-based outlier detection approach…
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Keywords:
nearest neighbors;
density;
outlier detection;
density based ... See more keywords
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Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.05.012
Abstract: Abstract Image outlier detection has been an important research issue for many computer vision tasks. However, most existing outlier detection methods fail in the high-dimensional image datasets. In order to address this problem, we propose…
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Keywords:
detection;
evolutionary multi;
multi objective;
image outlier ... See more keywords