A review on big data based on deep neural network approaches
Big data analytics has become a significant trend for many businesses as a result of the
daily acquisition of enormous volumes of data. This information has been gathered because …
daily acquisition of enormous volumes of data. This information has been gathered because …
Zero-touch networks: Towards next-generation network automation
The Zero-touch network and Service Management (ZSM) framework represents an
emerging paradigm in the management of the fifth-generation (5G) and Beyond (5G+) …
emerging paradigm in the management of the fifth-generation (5G) and Beyond (5G+) …
Enhanced prediction of parking occupancy through fusion of adaptive neuro-fuzzy inference system and deep learning models
While predicting parking occupancy is crucial for managing urban congestion, existing
models often exhibit gaps in accuracy, uncertainty handling, and integration potential. This …
models often exhibit gaps in accuracy, uncertainty handling, and integration potential. This …
A Survey on Deep Learning for Cellular Traffic Prediction
X Wang, Z Wang, K Yang, Z Song, C Bian… - Intelligent …, 2024 - spj.science.org
With the widespread deployment of 5G networks and the proliferation of mobile devices,
mobile network operators are confronted not only with massive data growth in mobile traffic …
mobile network operators are confronted not only with massive data growth in mobile traffic …
Cellular traffic prediction on blockchain-based mobile networks using LSTM model in 4G LTE network
V Kurri, V Raja, P Prakasam - Peer-to-Peer Networking and Applications, 2021 - Springer
The various demands from cellular users are increasing day by day. A tower can be selected
if the traffic through it at a specific time is predictable. Then a chosen set of issues can also …
if the traffic through it at a specific time is predictable. Then a chosen set of issues can also …
Traffic prediction for 5G: A deep learning approach based on lightweight hybrid attention networks
The maturity of 5G technology provides a guarantee for increasingly large communication
networks, while the resources required for communication and computation are also …
networks, while the resources required for communication and computation are also …
Analyzing the impact of outlier data points on multi-step internet traffic prediction using deep sequence models
The task of predicting Internet traffic is challenging, particularly in multi-step forecasting due
to the volatile and random nature of data. In addition, real-world traffic may contain outlier …
to the volatile and random nature of data. In addition, real-world traffic may contain outlier …
SafeCool: safe and energy-efficient cooling management in data centers with model-based reinforcement learning
J Wan, Y Duan, X Gui, C Liu, L Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Optimizing the cooling system plays a central role for capping the data center power
consumption. However, the performance of traditional cooling management strategies is not …
consumption. However, the performance of traditional cooling management strategies is not …
Noise prediction of chemical industry park based on multi-station Prophet and multivariate LSTM fitting model
With the gradual transformation of chemical industry park to digital and intelligent, various
types of environmental data in the park are extremely rich. It has high application value to …
types of environmental data in the park are extremely rich. It has high application value to …
Robustness analysis of hybrid machine learning model for anomaly forecasting in radio access networks
Quality of Service in mobile networks is a vigorous necessity that depends on the traffic
demand growth and the complex emergence of several new services and technologies. It …
demand growth and the complex emergence of several new services and technologies. It …