Results 21 to 30 of about 5,201 (163)
Jurnal Lebesgue, 2023 Indonesia's location on the "Ring of Fire" poses a high risk for seismic events. Addressing this, our study applied the Local Outlier Factor (LOF) algorithm for advanced seismic anomaly detection, crucial for geotectonic upheaval prediction.
Gregorius Airlangga
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Outlier detection algorithm based on k-nearest neighbors-local outlier factor
Journal of Algorithms & Computational Technology, 2022 The main task of outlier detection is to detect data objects which have a different mechanism from the conventional data set. The existing outlier detection methods are mainly divided into two directions: local outliers and global outliers. Aiming at the
He Xu, Lin Zhang, Peng Li, Feng Zhu
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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
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Implementation and assessment of two density-based outlier detection methods over large spatial point clouds [PDF]
, 2018 Several technologies provide datasets consisting of a large number of spatial points, commonly referred to as point-clouds. These point datasets provide spatial information regarding the phenomenon that is to be investigated, adding value through ...
Fissore, Francesca +3 more
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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
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IEEE Access, 2021 Deep Neural Networks (DNNs) are extensively deployed in today’s safety-critical autonomous systems thanks to their excellent performance. However, they are known to make mistakes unpredictably, e.g., a DNN may misclassify an object if it is used ...
Siyu Luan +4 more
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Abrupt user load change detection based on multiple features and LOF algorithm
Zhejiang dianli, 2023 The sudden load changes impact power grids by frequency and power oscillations. In order to distinguish the complex and massive abnormal user load data， this paper proposes a method combining multiple features and LOF （local outlier factor） algorithm ...
ZENG Jing +4 more
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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
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Classification under Streaming Emerging New Classes: A Solution using Completely Random Trees [PDF]
, 2016 This paper investigates an important problem in stream mining, i.e., classification under streaming emerging new classes or SENC. The common approach is to treat it as a classification problem and solve it using either a supervised learner or a semi ...
Mu, Xin, Ting, Kai Ming, Zhou, Zhi-Hua
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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
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