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Machine learning-based multi-target regression to effectively predict turning movements at signalized intersections
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Elsevier
, 2022 , Article)
Effective prediction of turning movement counts at intersections through efficient and accurate methods is essential and needed for various applications. Commonly predictive methods require extensive data collection, ...
A method of chained recommendation for charging piles in internet of vehicles
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Springer
, 2021 , Article)
With the popularization of new energy electric vehicles (EVs), the recommendation algorithm is widely used in the relatively new field of charge piles. At the same time, the construction of charging infrastructure is facing ...
Bayesian Beamforming for Mobile Millimeter Wave Channel Tracking in the Presence of DOA Uncertainty
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
This paper proposes a Bayesian approach for angle-based hybrid beamforming and tracking that is robust to uncertain or erroneous direction-of-arrival (DOA) estimation in millimeter wave (mmWave) multiple input multiple ...
Epidemic Risk Assessment by a Novel Communication Station Based Method
(
IEEE Computer Society
, 2022 , Article)
The COVID-19 pandemic has caused serious consequences in the last few months and trying to control it has been the most important objective. With effective prevention and control methods, the epidemic has been gradually ...
Systematic reviews in sentiment analysis: a tertiary study
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Springer Science and Business Media B.V.
, 2021 , Article)
With advanced digitalisation, we can observe a massive increase of user-generated content on the web that provides opinions of people on different subjects. Sentiment analysis is the computational study of analysing people's ...
Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
(
MDPI AG
, 2020 , Article)
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ...
Demand Response in HEMSs Using DRL and the Impact of Its Various Configurations and Environmental Changes
(
MDPI
, 2022 , Article)
With smart grid advances, enormous amounts of data are made available, enabling the training of machine learning algorithms such as deep reinforcement learning (DRL). Recent research has utilized DRL to obtain optimal ...
Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
(
Elsevier
, 2023 , Other)
Recently, developing automated video surveillance systems (VSSs) has become crucial to ensure the security and safety of the population, especially during events involving large crowds, such as sporting events. While ...
Ultrasound Intima-Media Complex (IMC) Segmentation Using Deep Learning Models
(
Multidisciplinary Digital Publishing Institute (MDPI)
, 2023 , Article)
Common carotid intima-media thickness (CIMT) is a common measure of atherosclerosis, often assessed through carotid ultrasound images. However, the use of deep learning methods for medical image analysis, segmentation and ...
A hybrid DNN-LSTM model for detecting phishing URLs
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Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
Phishing is an attack targeting to imitate the official websites of corporations such as banks, e-commerce, financial institutions, and governmental institutions. Phishing websites aim to access and retrieve users' important ...