Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Graph-based deep learning for communication networks: A survey
Communication networks are important infrastructures in contemporary society. There are
still many challenges that are not fully solved and new solutions are proposed continuously …
still many challenges that are not fully solved and new solutions are proposed continuously …
Multiple access techniques for intelligent and multifunctional 6G: Tutorial, survey, and outlook
Multiple access (MA) is a crucial part of any wireless system and refers to techniques that
make use of the resource dimensions (eg, time, frequency, power, antenna, code, and …
make use of the resource dimensions (eg, time, frequency, power, antenna, code, and …
Multi-scale adaptive graph neural network for multivariate time series forecasting
Multivariate time series (MTS) forecasting plays an important role in the automation and
optimization of intelligent applications. It is a challenging task, as we need to consider both …
optimization of intelligent applications. It is a challenging task, as we need to consider both …
Hybrid deep learning models for traffic prediction in large-scale road networks
Traffic prediction is an important component in Intelligent Transportation Systems (ITSs) for
enabling advanced transportation management and services to address worsening traffic …
enabling advanced transportation management and services to address worsening traffic …
Spatial-temporal cellular traffic prediction for 5G and beyond: A graph neural networks-based approach
During the past decade, Industry 4.0 has greatly promoted the improvement of industrial
productivity by introducing advanced communication and network technologies in the …
productivity by introducing advanced communication and network technologies in the …
Mobile traffic prediction in consumer applications: A multimodal deep learning approach
Mobile traffic prediction is an important yet challenging problem in consumer applications
because of the dynamic nature of user behavior, varying application quality of service (QoS) …
because of the dynamic nature of user behavior, varying application quality of service (QoS) …
Mvstgn: A multi-view spatial-temporal graph network for cellular traffic prediction
Timely and accurate cellular traffic prediction is difficult to achieve due to the complex spatial-
temporal characteristics of cellular traffic. The latest approaches mainly aim to model local …
temporal characteristics of cellular traffic. The latest approaches mainly aim to model local …
Large-scale cellular traffic prediction based on graph convolutional networks with transfer learning
Intelligent cellular traffic prediction is very important for mobile operators to achieve resource
scheduling and allocation. In reality, people often need to predict very large scale of cellular …
scheduling and allocation. In reality, people often need to predict very large scale of cellular …
A spatial-temporal transformer network for city-level cellular traffic analysis and prediction
With the accelerated popularization of 5G applications, accurate cellular traffic prediction is
becoming increasingly important for efficient network management. Currently, the latest …
becoming increasingly important for efficient network management. Currently, the latest …