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Fault diagnosis based on deep learning for current-carrying ring of catenary system in sustainable railway transportation
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Elsevier Ltd
, 2021 , Article)
In the intelligent traffic transportation, the security and stability are vital for the sustainable transportation and efficient logistics. The fault diagnosis on the catenary system is crucial for the railway transportation. ...
A deep learning-based approach for fault diagnosis of current-carrying ring in catenary system
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
In the Industrial Internet of Things, the deep learning-based methods are used to help solve various problems. The current-carrying ring as one of important components on the catenary system which is always small in the ...
Toward Reinforcement-Learning-Based Service Deployment of 5G Mobile Edge Computing with Request-Aware Scheduling
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
5G wireless network technology will not only significantly increase bandwidth but also introduce new features such as mMTC and URLLC. However, high request latency will remain a challenging problem even with 5G due to the ...
A CNN-Sequence-to-Sequence network with attention for residential short-term load forecasting
(
Elsevier
, 2022 , Article)
Residential short-term load forecasting has become an essential process to develop successful demand response strategies, and help utilities and customers optimize energy production and consumption. Most previous works ...
A deep learning based static taint analysis approach for IoT software vulnerability location
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Elsevier B.V.
, 2020 , Article)
Computer system vulnerabilities, computer viruses, and cyber attacks are rooted in software vulnerabilities. Reducing software defects, improving software reliability and security are urgent problems in the development of ...
An optimized algorithm for optimal power flow based on deep learning
(
Elsevier
, 2021 , Article)
With the increasing requirements for power system transient stability assessment, the research on power system transient stability assessment theory and methods requires not only qualitative conclusions about system transient ...
AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
(
Springer Nature
, 2022 , Article)
In theory, building automation and management systems (BAMSs) can provide all the components and functionalities required for analyzing and operating buildings. However, in reality, these systems can only ensure the control ...
Inpatient Discharges Forecasting for Singapore Hospitals by Machine Learning
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Hospitals can predetermine the admission rate and facilitate resource allocation based on valid emergency requests and bed capacity estimation. The excess unoccupied beds can be determined with the help of forecasting the ...
EEG-based emotion recognition using random Convolutional Neural Networks
(
Elsevier Ltd
, 2022 , Article)
Emotion recognition based on electroencephalogram (EEG) signals is helpful in various fields, including medical healthcare. One possible medical application is to diagnose emotional disorders in patients. Humans tend to ...
Random vector functional link neural network based ensemble deep learning for short-term load forecasting
(
Elsevier Ltd
, 2022 , Article)
Electric load forecasting is essential for the planning and maintenance of power systems. However, its un-stationary and non-linear properties impose significant difficulties in predicting future demand. This paper proposes ...