Performance evaluation of outlier detection techniques in production timeseries: A systematic review and meta-analysis
H Alimohammadi, SN Chen - Expert Systems with Applications, 2022 - Elsevier
Time-series data have been extensively collected and analyzed in many disciplines, such as
stock market, medical diagnosis, meteorology, and oil and gas industry. Numerous data in …
stock market, medical diagnosis, meteorology, and oil and gas industry. Numerous data in …
A survey on urban traffic anomalies detection algorithms
This paper reviews the use of outlier detection approaches in urban traffic analysis. We
divide existing solutions into two main categories: flow outlier detection and trajectory outlier …
divide existing solutions into two main categories: flow outlier detection and trajectory outlier …
Out-of-distribution detection with deep nearest neighbors
Abstract Out-of-distribution (OOD) detection is a critical task for deploying machine learning
models in the open world. Distance-based methods have demonstrated promise, where …
models in the open world. Distance-based methods have demonstrated promise, where …
Progress in outlier detection techniques: A survey
Detecting outliers is a significant problem that has been studied in various research and
application areas. Researchers continue to design robust schemes to provide solutions to …
application areas. Researchers continue to design robust schemes to provide solutions to …
A comparative study of prediction models for alkali-activated materials to promote quick and economical adaptability in the building sector
Alkali-activated materials (AAMs) have recently gained attention as potentially useful
alternative binders that can reduce carbon dioxide emissions initiated by the production of …
alternative binders that can reduce carbon dioxide emissions initiated by the production of …
A variational autoencoder solution for road traffic forecasting systems: Missing data imputation, dimension reduction, model selection and anomaly detection
Efforts devoted to mitigate the effects of road traffic congestion have been conducted since
1970s. Nowadays, there is a need for prominent solutions capable of mining information …
1970s. Nowadays, there is a need for prominent solutions capable of mining information …
Adapted k-nearest neighbors for detecting anomalies on spatio–temporal traffic flow
Outlier detection is an extensive research area, which has been intensively studied in
several domains such as biological sciences, medical diagnosis, surveillance, and traffic …
several domains such as biological sciences, medical diagnosis, surveillance, and traffic …
Improving the forecasting accuracy of interval-valued carbon price from a novel multi-scale framework with outliers detection: An improved interval-valued time series …
P Wang, Z Tao, J Liu, H Chen - Energy Economics, 2023 - Elsevier
Accurate carbon price forecasting can provide policymakers with a reasonable basis for
carbon pricing. Interval-valued carbon price forecasting could provide sufficient information …
carbon pricing. Interval-valued carbon price forecasting could provide sufficient information …
Temporal image analytics for abnormal construction activity identification
Abnormal activities on construction jobsites may compromise productivity and pose threat to
workers' safety. This paper proposes the analysis of consecutive image sequences for …
workers' safety. This paper proposes the analysis of consecutive image sequences for …
Identifying technology opportunity using SAO semantic mining and outlier detection method: A case of triboelectric nanogenerator technology
X Li, Y Wu, H Cheng, Q Xie, T Daim - Technological Forecasting and Social …, 2023 - Elsevier
With the high integration of science and technology development, how to early identify
technology opportunity is crucial for the governments' and enterprises' research and …
technology opportunity is crucial for the governments' and enterprises' research and …