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A comprehensive review on RSM-coupled optimization techniques and its applications
A Susaimanickam, P Manickam, AA Joseph - Archives of Computational …, 2023 - Springer
This review article provides a comprehensive analysis of the optimization techniques used
in a wide range of engineering applications. The comparison of various approaches such as …
in a wide range of engineering applications. The comparison of various approaches such as …
Video anomaly detection: A systematic review of issues and prospects
The increase in the deployment of surveillance camera in outdoor and indoor settings have
resulted in a growing demand for intelligent systems that can accurately detect and …
resulted in a growing demand for intelligent systems that can accurately detect and …
Enhancing short-term crime prediction with human mobility flows and deep learning architectures
Place-based short-term crime prediction models leverage the spatio-temporal patterns of
historical crimes to predict aggregate volumes of crime incidents at specific locations over …
historical crimes to predict aggregate volumes of crime incidents at specific locations over …
Fiber-optic telecommunication network wells monitoring by phase-sensitive optical time-domain reflectometer with disturbance recognition
The paper presents the application of a phase-sensitive optical time-domain reflectometer
(phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched …
(phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched …
ML-based inter-slice load balancing control for proactive offloading of virtual services
In the new 5G networking digital era, Network Slicing is pivotal in delivering new visionary
applications (eg, holographic calls, tactical Internet, immersive video, and expanded reality) …
applications (eg, holographic calls, tactical Internet, immersive video, and expanded reality) …
Distributed deep reinforcement learning based on bi-objective framework for multi-robot formation
J Li, Q Liu, G Chi - Neural Networks, 2024 - Elsevier
Improving generalization ability in multi-robot formation can reduce repetitive training and
calculation. In this paper, we study the multi-robot formation problem with the ability to …
calculation. In this paper, we study the multi-robot formation problem with the ability to …
Predicting buoyant jet characteristics: a machine learning approach
We study positively buoyant miscible jets through high-speed imaging and planar laser-
induced fluorescence methods, and we rely on supervised machine learning techniques to …
induced fluorescence methods, and we rely on supervised machine learning techniques to …
[HTML][HTML] Artificial general intelligence for the detection of neurodegenerative disorders
Parkinson's disease and Alzheimer's disease are among the most common
neurodegenerative disorders. These diseases are correlated with advancing age and are …
neurodegenerative disorders. These diseases are correlated with advancing age and are …
Second-law analysis of nanofluid-based photovoltaic/thermal system modeling and forecasting model based on artificial neural network
The PVT solar collectors can produce the thermal energy and power in a same frame. The
improvement of the PVT's efficiency leads to reducing the system size and capital costs. To …
improvement of the PVT's efficiency leads to reducing the system size and capital costs. To …
CyTFS: Cyber-Twin Fog System for Delay Efficient Task Offloading in 6G Mobile Networks
Sixth-generation (6G) mobile computing is a wireless, cutting-edge technology that is made
possible by the digital Interconnectedness of Everything (IoE). 6G connection depends on …
possible by the digital Interconnectedness of Everything (IoE). 6G connection depends on …