Anomaly detection in time series: a comprehensive evaluation
S Schmidl, P Wenig, T Papenbrock - Proceedings of the VLDB …, 2022 - dl.acm.org
Detecting anomalous subsequences in time series data is an important task in areas
ranging from manufacturing processes over finance applications to health care monitoring …
ranging from manufacturing processes over finance applications to health care monitoring …
Deep learning for time series anomaly detection: A survey
Time series anomaly detection has applications in a wide range of research fields and
applications, including manufacturing and healthcare. The presence of anomalies can …
applications, including manufacturing and healthcare. The presence of anomalies can …
Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series
S Sørbø, M Ruocco - Data Mining and Knowledge Discovery, 2024 - Springer
The field of time series anomaly detection is constantly advancing, with several methods
available, making it a challenge to determine the most appropriate method for a specific …
available, making it a challenge to determine the most appropriate method for a specific …
A hybrid ARIMA–WNN approach to model vehicle operating behavior and detect unhealthy states
As modern vehicles system becomes increasingly complex, there is an urgent need to
develop a framework to monitor the behavior and detect the unhealthy states to …
develop a framework to monitor the behavior and detect the unhealthy states to …
Passive ship detection and classification using hybrid cepstrums and deep compound autoencoders
The acoustic noise radiated from various ships in the same class is varying due to the
changing machinery regimes, the multi-path propagation effect, time-varying underwater …
changing machinery regimes, the multi-path propagation effect, time-varying underwater …
Application of WNN-PSO model in drought prediction at crop growth stages: A case study of spring maize in semi-arid regions of northern China
C Xiujia, Y Guanghua, G Jian, M Ningning… - … and Electronics in …, 2022 - Elsevier
Drought prediction of regional crops during the growth stages can get drought information in
advance and prepare for the response, so as to effectively guide the water-saving irrigation …
advance and prepare for the response, so as to effectively guide the water-saving irrigation …
Sustainable marine ecosystems: Deep learning for water quality assessment and forecasting
An appropriate management of the available resources within oceans and coastal regions is
vital to guarantee their sustainable development and preservation, where water quality is a …
vital to guarantee their sustainable development and preservation, where water quality is a …
A comparative study of series hybrid approaches to model and predict the vehicle operating states
M Alizadeh, J Ma - Computers & Industrial Engineering, 2021 - Elsevier
With the growing complexity of modern vehicle system, the capability of modeling the
behavior of different subsystems and predicting their forthcoming patterns become vital. It …
behavior of different subsystems and predicting their forthcoming patterns become vital. It …
Privileged information-driven random network based non-iterative integration model for building energy consumption prediction
H Sun, W Zhai, Y Wang, L Yin, F Zhou - Applied Soft Computing, 2021 - Elsevier
Accurate building energy consumption (BEC) prediction plays an increasingly significant
role in energy control and conservation. However, owing to the high level of randomness of …
role in energy control and conservation. However, owing to the high level of randomness of …
Random finite set-based anomaly detection for safety monitoring in construction sites
Low visibility hazard detection in construction sites is a crucial task for prevention of fatal
accidents. Manual monitoring of construction workers to ensure they follow the safety rules …
accidents. Manual monitoring of construction workers to ensure they follow the safety rules …