Recognition of Power Quality Disturbance Based on RCNN
R Fan, H Li, H Xiao, H Wang, L Qi - Journal of Physics …, 2022 - iopscience.iop.org
With the development of the smart grid, the problem of power quality disturbance is
becoming more and more serious. To improve the classification ability of power quality …
becoming more and more serious. To improve the classification ability of power quality …
Power quality prediction of active distribution network based on CNN-LSTM deep learning model
L Hua - International Conference on Artificial Intelligence for …, 2021 - Springer
Aiming at the sequential and non-linear characteristics of power quality data over a long
time span, a set of PQ evaluation and early warning system with DG distribution network …
time span, a set of PQ evaluation and early warning system with DG distribution network …
An empirical study on using CNNs for fast radio signal prediction
Accurate radio frequency power prediction in a geographic region is a computationally
expensive part of finding the optimal transmitter location using a ray tracing software. We …
expensive part of finding the optimal transmitter location using a ray tracing software. We …
A new method for radio wave propagation prediction based on bp-neural network and path loss model
Y Wang, MY Liang, J Hu, T Song - 2020 12th International …, 2020 - ieeexplore.ieee.org
In this paper, a new method for radio wave propagation prediction based on BP neural
network and simplified path loss model is proposed. The method is based on a large amount …
network and simplified path loss model is proposed. The method is based on a large amount …
Variational autoencoder assisted neural network likelihood RSRP prediction model
Measuring customer experience on mobile data is of utmost importance for global mobile
operators. The reference signal received power (RSRP) is one of the important indicators for …
operators. The reference signal received power (RSRP) is one of the important indicators for …
Highly accurate prediction of radio propagation using model classifier
K Katagiri, K Onose, K Sato, K Inage… - 2019 IEEE 89th …, 2019 - ieeexplore.ieee.org
In this paper, we propose a measurement-based spectrum database using model classifier.
In the radio propagation, path loss is the fundamental factor to recognize the coverage area …
In the radio propagation, path loss is the fundamental factor to recognize the coverage area …
[HTML][HTML] A comparative study of predicting the availability of power line communication nodes using machine learning
Abstract Power Line Communication technology uses power cables to transmit data.
Knowing whether a node is working in advance without testing saves time and resources …
Knowing whether a node is working in advance without testing saves time and resources …
Comprehensive early warning of power quality in distribution network based on deep learning
L Hua - Wireless Networks, 2023 - Springer
Aiming at the sequential and nonlinear characteristics of power quality data over a long time
span, a set of PQ evaluation and early warning system on DG distribution network based on …
span, a set of PQ evaluation and early warning system on DG distribution network based on …
Deep Learning Models Classify and Detect Direct Current Power Quality Issues for Grid Operation Implications
HH Goh, H Xu, Z Dongdong, W Dai, SY Wong… - Available at SSRN … - papers.ssrn.com
Abstract In Direct Current (DC) power systems, the introduction of new energy generation
and non-linear loads can result in power quality disturbances, which can deteriorate the …
and non-linear loads can result in power quality disturbances, which can deteriorate the …