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Forecasting the Behavior of Gas Furnace Multivariate Time Series Using Ridge Polynomial Based Neural Network Models
In this paper, a new application of ridge polynomial based neural network models in multivariate time series forecasting is presented. The existing ridge polynomial based neural network models can be grouped into two groups. ...
Data imputation analysis for Cosmic Rays time series
(Elsevier, 2020)
Estimación del consumo eléctrico colombiano en el corto y largo plazo empleando regresión multivariable y series temporales
(Universidad de La Salle. Facultad de Ingeniería. Ingeniería Eléctrica, 2016)
Mining multivariate time-series for anomaly detection in mobile networks on the usage of variational auto encoders and dilated convolutions
(ACM, 2022)
The automatic detection of anomalies in communication networks plays a central role in network management. Despite the many attempts and approaches for anomaly detection explored in the past, the detection of rare events ...
Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach
(2019-06)
Based on a General Dynamic Factor Model with infinite-dimensional factor space, we develop a new estimation and forecasting procedures for conditional covariance matrices in high-dimensional time series. The performance ...