CAE: Contextual auto-encoder for multivariate time-series anomaly detection in air transportation
Abstract The Automatic Dependent Surveillance-Broadcast protocol is one of the latest
compulsory advances in air surveillance. While it supports the tracking of the ever-growing …
compulsory advances in air surveillance. While it supports the tracking of the ever-growing …
Multi-attribute graph convolution network for regional traffic flow prediction
In recent years, traffic flow prediction has been extensively explored in Intelligent
Transportation Systems, which is beneficial for reducing traffic jams and accidents as well as …
Transportation Systems, which is beneficial for reducing traffic jams and accidents as well as …
Short term solar power and temperature forecast using recurrent neural networks
V Gundu, SP Simon - Neural processing letters, 2021 - Springer
Solar energy is one of the world's clean and renewable source of energy and it is an
alternative power with the ability to serve a greater proportion of rising demand needs. The …
alternative power with the ability to serve a greater proportion of rising demand needs. The …
On the challenges of global entity-aware deep learning models for groundwater level prediction
B Heudorfer, T Liesch, S Broda - Hydrology and Earth System …, 2023 - hess.copernicus.org
The application of machine learning (ML) including deep learning models in hydrogeology
to model and predict groundwater level in monitoring wells has gained some traction in …
to model and predict groundwater level in monitoring wells has gained some traction in …
Forecasting the mid-price movements with high-frequency lob: a dual-stage temporal attention-based deep learning architecture
Y Guo, X Chen - Arabian Journal for Science and Engineering, 2023 - Springer
Effectively forecasting the stock mid-price movements based on Limit Order Book (LOB) data
is crucial for issuing the right trade instructions in an automated trading market. The LOB …
is crucial for issuing the right trade instructions in an automated trading market. The LOB …
Blood glucose forecasting from temporal and static information in children with T1D
Background The overarching goal of blood glucose forecasting is to assist individuals with
type 1 diabetes (T1D) in avoiding hyper-or hypoglycemic conditions. While deep learning …
type 1 diabetes (T1D) in avoiding hyper-or hypoglycemic conditions. While deep learning …
Electric vehicle energy consumption prediction for unknown route types using deep neural networks by combining static and dynamic data
H Yılmaz, B Yagmahan - Applied Soft Computing, 2024 - Elsevier
Accurate energy consumption prediction of electric vehicles (EVs) is crucial for drivers
considering long trips. All the data should be provided beforehand to determine the energy …
considering long trips. All the data should be provided beforehand to determine the energy …
Predicting a time-dependent quantity using recursive generative query network
G Miebs, M Wójcik, A Karaszewski… - … Journal of Neural …, 2022 - World Scientific
We propose here a novel neural architecture dedicated to the prediction of time series. It can
be considered as an adaptation of the idea of (GQN) to the data which is of a sequence …
be considered as an adaptation of the idea of (GQN) to the data which is of a sequence …
[HTML][HTML] Predictive modeling of morbidity and mortality in patients hospitalized with COVID-19 and its clinical implications: algorithm development and interpretation
Background: The COVID-19 pandemic began in early 2021 and placed significant strains on
health care systems worldwide. There remains a compelling need to analyze factors that are …
health care systems worldwide. There remains a compelling need to analyze factors that are …
Evaluation of deep learning models for Australian climate extremes: prediction of streamflow and floods
S Khedkar, RW Vervoort, R Chandra - arXiv preprint arXiv:2407.15882, 2024 - arxiv.org
In recent years, climate extremes such as floods have created significant environmental and
economic hazards for Australia, causing damage to the environment and economy and …
economic hazards for Australia, causing damage to the environment and economy and …