Results 31 to 40 of about 5,201 (163)
, 2019 In recent years, there have been many practical applications of anomaly detection such as in predictive maintenance, detection of credit fraud, network intrusion, and system failure. The goal of anomaly detection is to identify in the test data anomalous
Chaudhuri, Arin +2 more
core +1 more source
Applied Computational Intelligence and Soft Computing, 2022 Data clustering algorithms experience challenges in identifying data points that are either noise or outlier. Hence, this paper proposes an enhanced connectivity measure based on the outlier detection approach for multi-objective data clustering problems.
Hossam M. J. Mustafa, Masri Ayob
doaj +1 more source
Using hardware performance counters for fault localization [PDF]
, 2010 In this work, we leverage hardware performance counters-collected data as abstraction mechanisms for program executions and use these abstractions to identify likely causes of failures.
Yılmaz, Cemal, Yilmaz, Cemal
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ADASYN-LOF Algorithm for Imbalanced Tornado Samples
Atmosphere, 2022 Early warning and forecasting of tornadoes began to combine artificial intelligence (AI) and machine learning (ML) algorithms to improve identification efficiency in the past few years.
Zhipeng Qing +5 more
doaj +1 more source
Log-based Anomaly Detection of CPS Using a Statistical Method
, 2017 Detecting anomalies of a cyber physical system (CPS), which is a complex system consisting of both physical and software parts, is important because a CPS often operates autonomously in an unpredictable environment.
Choi, Eun-Hye +3 more
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Measuring the Influence of Observations in HMMs through the Kullback-Leibler Distance
, 2012 We measure the influence of individual observations on the sequence of the hidden states of the Hidden Markov Model (HMM) by means of the Kullback-Leibler distance (KLD).
Nuel, Gregory, Perduca, Vittorio
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Adapted K-Nearest Neighbors for Detecting Anomalies on Spatio–Temporal Traffic Flow [PDF]
, 2019 Outlier detection is an extensive research area, which has been intensively studied in several domains such as biological sciences, medical diagnosis, surveillance, and traffic anomaly detection. This paper explores advances in the outlier detection area
Belhadi, Asma +4 more
core +3 more sources
A new non-parametric detector of univariate outliers for distributions with unbounded support
, 2017 The purpose of this paper is to construct a new non-parametric detector of univariate outliers and to study its asymptotic properties. This detector is based on a Hill's type statistic.
Bardet, Jean-Marc +1 more
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Fibroblast Transcriptomics in Molecular Diagnostics of a Comprehensive Dystonia Cohort
Annals of Neurology, EarlyView.Objective Genomic sequencing leaves >50% of dystonia‐affected individuals without a diagnosis. Where DNA‐oriented approaches remain insufficient, integrating multiomics is essential to advance genome interpretation. Herein, we incorporated RNA sequencing (RNA‐seq) data from 167 patients with dystonia across a range of ages and presentations. Methods We
Alice Saparov +42 more
wiley +1 more source
Outlier Detection in Ocean Wave Measurements by Using Unsupervised Data Mining Methods
Polish Maritime Research, 2018 Outliers are considerably inconsistent and exceptional objects in the data set that do not adapt to expected normal condition. An outlier in wave measurements may be due to experimental and configuration errors, technical defects in equipment ...
Mahmoodi Kumars, Ghassemi Hassan
doaj +1 more source