Results 11 to 20 of about 1,104 (139)
Fast Outlier Detection Using a Grid-Based Algorithm. [PDF]
PLoS ONE, 2016 As one of data mining techniques, outlier detection aims to discover outlying observations that deviate substantially from the reminder of the data. Recently, the Local Outlier Factor (LOF) algorithm has been successfully applied to outlier detection ...
Jihwan Lee, Nam-Wook Cho
doaj +1 more source
IEEE Access, 2021 In the hot rolling process, the prediction of strip crown is the key factor to improve the flatness quality of the strip. However, the traditional prediction method can only provide prediction values, but does not quantitatively evaluate the prediction ...
Yan Wu, Xu Li, Feng Luan, Yaodong He
doaj +1 more source
Detection of Outliers in Univariate Circular Data by Means of the Outlier Local Factor (LOF) [PDF]
Statistics in Transition New Series, 2020 Abstract The problem of outlier detection in univariate circular data was the object of increased interest over the last decade. New numerical and graphical methods were developed for samples from different circular probability distributions.
openaire +2 more sources
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
doaj +1 more source
TADILOF: Time Aware Density-Based Incremental Local Outlier Detection in Data Streams
Sensors, 2020 Outlier detection in data streams is crucial to successful data mining. However, this task is made increasingly difficult by the enormous growth in the quantity of data generated by the expansion of Internet of Things (IoT).
Jen-Wei Huang +2 more
doaj +1 more source
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
doaj +1 more source
Robust Incremental Outlier Detection Approach Based on a New Metric in Data Streams
IEEE Access, 2021 Detecting outliers in real time from multivariate streaming data is a vital and challenging research topic in many areas. Recently introduced the incremental Local Outlier Factor (iLOF) approach and its variants have received considerable attention as ...
Ali Degirmenci, Omer Karal
doaj +1 more source
Clustering-Based Outlier Detection Technique Using PSO-KNN
Journal of Applied Science and Engineering, 2023 In this work, we present an unsupervised machine learning algorithm for outlier detection by integrating Particle Swarm Optimization (PSO) and the K-nearest neighbor (KNN) technique.
Sushilata D. Mayanglambam +2 more
doaj +1 more source
A Comparative Study for Outlier Detection Strategies Based On Traditional Machine Learning For IoT Data Analysis. [PDF]
IJCI International Journal of Computers and Information, 2022 Internets of Things (IoT) systems are increasing very fast. They have different types of wireless sensor networks (WSN) behind them. These networks have many applications that are a portion of our life such as healthcare, agricultural, mechanical, and ...
Khalid Amin +2 more
doaj +1 more source
An Analysis of ML-Based Outlier Detection from Mobile Phone Trajectories
Future Internet, 2022 This paper provides an analysis of two machine learning algorithms, density-based spatial clustering of applications with noise (DBSCAN) and the local outlier factor (LOF), applied in the detection of outliers in the context of a continuous framework for
Francisco Melo Pereira, Rute C. Sofia
doaj +1 more source