Impact of word embedding models on text analytics in deep learning environment: a review
The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
[HTML][HTML] Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review
Z Lv, W Shang - Green Technologies and Sustainability, 2023 - Elsevier
With the development of smart cities, new requirements have been put forward for the
control of carbon emissions (CEs) in the transportation system. Intelligent transportation …
control of carbon emissions (CEs) in the transportation system. Intelligent transportation …
CorrAUC: a malicious bot-IoT traffic detection method in IoT network using machine-learning techniques
Identification of anomaly and malicious traffic in the Internet-of-Things (IoT) network is
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …
Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city
Identifying cyber attacks traffic is very important for the Internet of things (IoT) security in
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
A VMD and LSTM based hybrid model of load forecasting for power grid security
As the basis for the static security of the power grid, power load forecasting directly affects
the safety of grid operation, the rationality of grid planning, and the economy of supply …
the safety of grid operation, the rationality of grid planning, and the economy of supply …
Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges
Federated learning (FL) plays an important role in the development of smart cities. With the
evolution of big data and artificial intelligence, issues related to data privacy and protection …
evolution of big data and artificial intelligence, issues related to data privacy and protection …
A novel web attack detection system for internet of things via ensemble classification
Internet of Things (IoT) has become one of the fastest-growing technologies and has been
broadly applied in various fields. IoT networks contain millions of devices with the capability …
broadly applied in various fields. IoT networks contain millions of devices with the capability …
An efficient edge computing management mechanism for sustainable smart cities
Since ancient times, humanity has envisioned a world where people and things connect and
interact. The advent of generation mobile systems, the so-called 5 G in the early century, has …
interact. The advent of generation mobile systems, the so-called 5 G in the early century, has …
Deep reinforcement learning for partially observable data poisoning attack in crowdsensing systems
M Li, Y Sun, H Lu, S Maharjan… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Crowdsensing systems collect various types of data from sensors embedded on mobile
devices owned by individuals. These individuals are commonly referred to as workers that …
devices owned by individuals. These individuals are commonly referred to as workers that …
An edge computing based anomaly detection method in IoT industrial sustainability
X Yu, X Yang, Q Tan, C Shan, Z Lv - Applied Soft Computing, 2022 - Elsevier
In recent years, the evolving Internet of Things (IoT) technology has been widely used in
various industrial scenarios, whereby massive sensor data involving both normal data and …
various industrial scenarios, whereby massive sensor data involving both normal data and …