A hybrid prediction method for realistic network traffic with temporal convolutional network and LSTM
Accurate and real-time prediction of network traffic can not only help system operators
allocate resources rationally according to their actual business needs but also help them …
allocate resources rationally according to their actual business needs but also help them …
Large-scale network traffic prediction with LSTM and temporal convolutional networks
Real-time and precise prediction for traffic of networks is critically important for allocating the
optimal computing/network resources based on users' business requirements, analyzing the …
optimal computing/network resources based on users' business requirements, analyzing the …
[HTML][HTML] Link quality prediction in wireless community networks using deep recurrent neural networks
Wireless community networks (WCNs) are large, heterogeneous, dynamic, and
decentralized networks. Such complex characteristics raise different challenges, such as the …
decentralized networks. Such complex characteristics raise different challenges, such as the …
An improved attention-based LSTM for multi-step dissolved oxygen prediction in water environment
The prediction of accurate water quality has great significance to the sustainable
management of water resources and pollution prevention. Due to the complexity of water …
management of water resources and pollution prevention. Due to the complexity of water …
A study on diverse methods and performance measures in sentiment analysis
With the vast development of Internet technology 2.0, millions of people share their opinions
on different social networking sites. To obtain the necessary information from the large …
on different social networking sites. To obtain the necessary information from the large …
Hybrid Water Quality Prediction with Frequency Domain Conversion Enhancement and Seasonal Decomposition
Water quality prediction can accurately reflect the development trend of water quality, and it
is an important means to prevent the water environment from being polluted and maintain …
is an important means to prevent the water environment from being polluted and maintain …
Bi-objective intelligent task scheduling for green clouds with deep learning-based prediction
The ever-increasing deployment of cloud data centers causes high energy consumption,
high cost, and harmful environmental pollution. To solve above problems, cloud service …
high cost, and harmful environmental pollution. To solve above problems, cloud service …
A Deep Learning Approach to Large-Scale Light Curve Prediction and Real-Time Anomaly Detection with Grubbs Criterion
X Huang, L Peng, C Lu, J Bi… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
In light curves (LCs), the brightness of stars is associated with time, and so is its image. The
traditional data processing methods cannot effectively handle real-time and large-volume …
traditional data processing methods cannot effectively handle real-time and large-volume …