The number of Internet of Things (IoT)-based applications is constantly increasing, and transferring all their associated data to a remote centralized cloud requires more latency …
Q Huang, R Gao, H Akhavan - Pattern Recognition, 2023 - Elsevier
Ensemble clustering has emerged as a combination of several basic clustering algorithms to achieve high quality final clustering. However, this technique is challenging due to the …
R Kumar Pandey, A Kumar… - Journal of Energy …, 2022 - asmedigitalcollection.asme.org
The deep learning model constituting two neural network models (ie, densely connected and long short-term memory) has been applied for automatic characterization of dual …
HP Li, ME Kordi - Internet of Things, 2023 - Elsevier
This study configures an architecture based on Deep Reinforcement Learning (DRL) with the aim of providing online services to end users in Mobile Edge Computing (MEC) …
Lung Cancer is one of the primary causes of cancer-related deaths worldwide. Timely diagnosis and precise staging are pivotal for treatment planning, and thus can lead to …
The current literature on public perceptions of autonomous vehicles focuses on potential users and the target market. However, autonomous vehicles need to operate in a mixed …
One of the common techniques to reduce the scalability problem in collaborative filtering (CF)-based recommender systems is the clustering technique, which accelerates finding the …
S Li, S Fu, D Zheng - Sustainability, 2022 - mdpi.com
A rural built-up area is one of the most important features of rural regions. Rapid and accurate extraction of rural built-up areas has great significance to rural planning and …
An extremely high number of geographically dispersed, energy‐limited sensor nodes make up wireless sensor networks. One of the critical difficulties with these networks is their …