Results 11 to 20 of about 98,857 (165)
An Outlier Detection Approach Based on Improved Self-Organizing Feature Map Clustering Algorithm
IEEE Access, 2019 Local Outlier Factor (LOF) outlier detecting algorithm has good accuracy in detecting global and local outliers. However, the algorithm needs to traverse the entire dataset when calculating the local outlier factor of each data point, which adds extra ...
Ping Yang +4 more
doaj +3 more sources
Design and analysis of management platform based on financial big data [PDF]
PeerJ Computer Science, 2023 Traditional financial accounting will become limited by new technologies which are unable to meet the market development. In order to make financial big data generate business value and improve the information application level of financial management ...
Yuhua Chen +3 more
doaj +2 more sources
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
Energy Reports, 2023 The missing and abnormal data in power transformer operation and monitoring greatly affect the accuracy of fault diagnosis and thus threaten the stable operation of power systems.
Dexu Zou +9 more
doaj +1 more source
A new outlier detection algorithm based on observation-point mechanism
Shenzhen Daxue xuebao. Ligong ban, 2022 Outlier detection is an important branch of data mining research, and has wide applications in the fields of finance, telecommunications, and biology. The traditional nearest neighbor-based outlier detection (NNOD) and local outlier factor-based outlier ...
YU Wanguo, HE Yulin, QIN Huilin
doaj +1 more source
Unsupervised Outlier Detection Mechanism for Tea Traceability Data
IEEE Access, 2022 The presence of outliers in tea traceability data can mislead customers and have a significant impact on the reputation and profits of tea companies. To solve this problem, an unsupervised outlier detection mechanism for tea traceability data is proposed.
Honggang Yang +4 more
doaj +1 more source
Entropy, 2023 Outlier detection is an important task in the field of data mining and a highly active area of research in machine learning. In industrial automation, datasets are often high-dimensional, meaning an effort to study all dimensions directly leads to data ...
Zihao Li, Liumei Zhang
doaj +1 more source
Measuring Novelty in Autonomous Vehicles Motion Using Local Outlier Factor Algorithm
, 2021 Under unexpected conditions or scenarios, autonomous vehicles (AV) are more likely to follow abnormal unplanned actions, due to the limited set of rules or amount of experience they possess at that time. Enabling AV to measure the degree at which their movements are novel in real-time may help to decrease any possible negative consequences.
Alsawadi, Hassan, Bilal, Muhammad
openaire +2 more sources
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
Density-Distance Outlier Detection Algorithm Based on Natural Neighborhood
Axioms, 2023 Outlier detection is of great significance in the domain of data mining. Its task is to find those target points that are not identical to most of the object generation mechanisms.
Jiaxuan Zhang, Youlong Yang
doaj +1 more source