Recurrent Neural Network-based Base Transceiver Station
This work investigates the early prediction of BTS failures due to power system and environmental abnormalities using recurrent neural networks (RNN) with long short term
The Unsung Hero of Telecom Energy: Why Base Station Power
As a key component of intelligent and unmanned base station maintenance, this system continuously safeguards the power supply and environmental conditions of telecom
Power supply station equipment status monitoring and evaluation
Monitoring and analyzing the operation status of power equipment in power supply stations is of great significance for ensuring power supply safety, improving power supply
Prediction of Base Transceiver Station Power Supply System
This study is dedicated to predicting potential failure indicators in BTS power systems using deep neural network architectures, such as recurrent and convolutional neural networks.
Power supply station equipment status monitoring and evaluation system
Monitoring and analyzing the operation status of power equipment in power supply stations is of great significance for ensuring power supply safety, improving power supply
(PDF) A Comprehensive Review on the Role of Artificial
The paper reviews various intelligent methods used in power system analysis, emphasizing their roles in predictive maintenance, fault detection, real-time control, and
Optimization of Communication Base Station Battery
In the communication power supply field, base station interruptions may occur due to sudden natural disasters or unstable power supplies. This work studies the optimization of
Management and maintenance of base station switching power supply
The monitoring module is an intelligent device in the high-frequency switching power supply system, which manages the operation of the switching power supply system in a
CN113178925A
The invention relates to the technical field of power supply management of a communication base station, in particular to an intelligent power supply state detection method and...
Optimization of Communication Base Station
In the communication power supply field, base station interruptions may occur due to sudden natural disasters or unstable
ADDIS ABABA UNIVERSITY ADDIS ABABA INSTITUTE OF
To identify the most significant factors affecting BTS power supply systems, focusing on environmental factors, equipment failure, and power supply issues: The study aims to identify
Machine learning for base transceiver stations power failure
We employ a combination of deep learning architectures, including Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and hybrid CNN-LSTM
(PDF) A Comprehensive Review on the Role of
The paper reviews various intelligent methods used in power system analysis, emphasizing their roles in predictive maintenance, fault
The Unsung Hero of Telecom Energy: Why Base Station Power Systems
As a key component of intelligent and unmanned base station maintenance, this system continuously safeguards the power supply and environmental conditions of telecom
Management and maintenance of base station
The monitoring module is an intelligent device in the high-frequency switching power supply system, which manages the operation
Recurrent Neural Network-based Base Transceiver Station Power Supply
This work investigates the early prediction of BTS failures due to power system and environmental abnormalities using recurrent neural networks (RNN) with long short term