Results 31 to 40 of about 225,629 (280)
Fault diagnosis of lithium-ion battery energy storage systems based on local outlier factor
Zhejiang dianli, 2023 Lithium-ion batteries may lead to fire and other accidents when working under overcharge， high temperature， and external short circuits. The faults can be prevented from escalating to thermal runaway through early fault diagnosis and fault location of ...
PENG Peng +5 more
doaj +1 more source
Hybrid Machine Learning–Statistical Method for Anomaly Detection in Flight Data
Applied Sciences, 2022 This paper investigates the use of an unsupervised hybrid statistical–local outlier factor algorithm to detect anomalies in time-series flight data. Flight data analysis is an activity carried out by airlines primarily as a means of improving the safety ...
Sameer Kumar Jasra +3 more
doaj +1 more source
A geometrical analysis of global stability in trained feedback networks [PDF]
, 2019 Recurrent neural networks have been extensively studied in the context of neuroscience and machine learning due to their ability to implement complex computations. While substantial progress in designing effective learning algorithms has been achieved in
Mastrogiuseppe, Francesca +1 more
core +2 more sources
A subsampling method for the computation of multivariate estimators with high breakdown point [PDF]
, 1994 All known robust location and scale estimators with high breakdown point for multivariate sample's are very expensive to compute. In practice, this computation has to be carried out using an approximate subsampling procedure.
Juan, Jesús, Prieto, Francisco J.
core +5 more sources
Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor
Journal of Engineering Science and Technology Review, 2015 Spatial local outlier factor (SLOF) algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO 2 monitoring data obtained in the carbon capture and storage (CCS) project, the K-Nearest Neighbour (KNN) graph was constructed using ...
Liu Xin, Zhang Shaoliang, Zheng Pulin
openaire +1 more source
Optimasi Pengelompokan Data Pada Metode K-means dengan Analisis Outlier
Jurnal Teknologi dan Sistem Informasi, 2019 Data mining secara umum adalah proses analisis dan eksplorasi sejumlah besar data yang berbeda untuk menemukan pola yang bermakna. . Berbagai teknik tersedia dalam data mining untuk ekstraksi pengetahuan antara lain klasifikasi, prediksi, estimasi ...
Pasek Agus Ariawan
doaj +1 more source
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
core +3 more sources
, 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
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
An adaptive smartphone anomaly detection model based on data mining
EURASIP Journal on Wireless Communications and Networking, 2018 With the popularization of smartphones, they have become the main target of malicious applications. In recent years, malware has become a major threat to Android smartphones.
Xue Li Hu +2 more
doaj +1 more source