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Transfer learning based dynamic security assessment
2021
IET Generation, Transmission & Distribution
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However, excessive update training is one of the constraints for ANN to be effectively performed at pre-fault and post-fault operations on online DSA. ...
for smart grid and smart metering environment, online dynamic security assessment (DSA) plays a key role for early unstable event detection on power system security. ...
The non-electrical feature dataset on ImageNet is used to improve the performance for an AI model training on the power system. 2. ...
doi:10.1049/gtd2.12181
fatcat:2xgepy3isvhf5euuqpvgtgtwam
Semi-ProtoPNet Deep Neural Network for the Classification of Defective Power Grid Distribution Structures
2022
Sensors
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To improve the reliability of the network, visual inspections of the electrical power system can be carried out; these inspections can be automated using computer vision techniques based on deep neural ...
Based on this need, this paper proposes the Semi-ProtoPNet deep learning model to classify defective structures in the power distribution networks. ...
Techniques based on deep learning are becoming increasingly popular for the identification of faults in electrical power networks [39] . Fahim et al. ...
doi:10.3390/s22134859
pmid:35808353
pmcid:PMC9269338
fatcat:odb2n25qkvbflme6yf63iqx6ny
Estimation of Wind Turbine Angular Velocity Remotely Found on Video Mining and Convolutional Neural Network
2020
Applied Sciences
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For this purpose, we have used SSD (Single Shot Multi-Box Detector) object detection algorithm and some specific classification methods based on DenseNet, SqueezeNet, ResNet50, and InceptionV3 models. ...
Its strong performance in computer vision problems has conducted us to provide a high accuracy intelligent machine vision system based on deep learning to estimate the wind turbine angular velocity, remotely ...
In the emerging power networks, so-called smart grids (SGs) [6] [7] [8] , advanced communication network infrastructures [8] [9] [10] [11] [12] [13] [14] along with two-way power flows provide appropriate ...
doi:10.3390/app10103544
fatcat:okwlhmgdw5expkdpzvsxl4xdaa
Falcon: A Novel Chinese Short Text Classification Method
2018
Journal of Computer and Communications
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In order to express text directly, a simple but new variation which employs one-hot with low-dimension was proposed. In this paper, a Densenet-based model was proposed to short text classification. ...
From our experimental results, the Falcon method obtained significant improvements in the state-of-art models on most of them in all respects, especially in the first experiment of error rate. ...
Conclusions In this paper, this is the first time that a novel short text classification method based on Densenet networks was proposed to address the electric power complaint text. ...
doi:10.4236/jcc.2018.611021
fatcat:fgnlnh3tobhghng7fpt7v3qaia
2019 6th International Conference on Systems and Informatics
2019
2019 6th International Conference on Systems and Informatics (ICSAI)
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Great efforts have been made to improve the state of the art in the technologies for computer-based applications. ...
These submissions cover various related areas, such as Control and Automation Systems, Power and Energy Systems, Intelligent Systems, Computer Systems and Applications, Communications and Networking, Image ...
Drive of Single-Phase Generator Fault Analysis of Wind Turbine Gearbox Based on Vague Set and Fault Tree Low-Frequency Oscillation Mode Identification with OpenPDC Platform Fuel Cells and Electrical Vehicles ...
doi:10.1109/icsai48974.2019.9010230
fatcat:eovojg6yirhfhnmxzugrvzzc5a
Seismic-Net: A Deep Densely Connected Neural Network to Detect Seismic Events
[article]
2018
arXiv
pre-print
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In this work, we develop a novel machine-learning detection package, named "Seismic-Net", which is based on the deep densely connected neural network. ...
Traditional leakage detection and monitoring techniques rely on geophysical observations including seismic. ...
In this work, we built our model upon the densely connected block [13] (DenseNet), which is an improved version of ResNet. ...
arXiv:1802.02241v1
fatcat:tdjo7zhpjvdcbctztn5rhw5z7m
Table of Contents
2020
2020 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)
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Jagtap, Mausam Sharma 191 GA based Simultaneous Optimization of hybrid Distributed Generation in the Power System Network P. Shanmugapriya, J Baskaran, C. ...
Iris Presentation attacks and detection based on
Generative Adversarial Network
Meenakshi K, G. ...
doi:10.1109/icpects49113.2020.9337048
fatcat:s3dd7467p5bwhgcbqnnkv3gyfm
DisaggRec: Architecting Disaggregated Systems for Large-Scale Personalized Recommendation
[article]
2022
arXiv
pre-print
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Moreover, through in-depth characterization, we reveal that the monolithic server-based cluster suffers resource idleness and wastes up to 30% TCO by provisioning resources in fixed proportions. ...
Deep learning-based personalized recommendation systems are widely used for online user-facing services in production datacenters, where a large amount of hardware resources are procured and managed to ...
Then, DenseNet is launched on the GPU to calculate the final prediction. Handling Failures. ...
arXiv:2212.00939v1
fatcat:mdb5bdnhubbyfig6cfnlmbawgy
2021 Index IEEE Transactions on Intelligent Transportation Systems Vol. 22
2021
IEEE transactions on intelligent transportation systems (Print)
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-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
Note that the item title is found only under the primary entry in the Author Index. ...
Models.Zhou, J., +, TITS Dec. 2021 7561-7572 Speed Prediction Based on a Traffic Factor State Network Model.Zhang, W., +, TITS May 2021 3112-3122 State of Power Prediction for Lithium-Ion Batteries in ...
doi:10.1109/tits.2021.3139738
fatcat:p2mkawtrsbaepj4zk24xhyl2oa
Automated monitoring of construction sites of electric power substations using deep learning
2021
IEEE Access
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To achieve the main objective, a comparison was made among four convolutional neural network architectures: DenseNet, Inception, ResNet, and SqueezeNet, in the classification task. ...
With each passing year, the consumption of electric energy in Brazil and the world increases, making it necessary to adopt measures such as the construction of new plants and the installation of power ...
In recent years, several solutions have emerged for the monitoring of electric power substations, most of them based on computer vision and digital image processing algorithms. ...
doi:10.1109/access.2021.3054468
fatcat:5xwdwygqorgexlno2ez5lu3npa
Technical Session Schedule
2021
2021 Innovations in Power and Advanced Computing Technologies (i-PACT)
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VEHICLE CHARGING STATION USING HOMER GRID STABILITY IMPROVEMENT OF POWER SYSTEM WITH WIND INTEGRATION BASED ON L-INDEX MAXIMUM POWER TRACKING UNDER COMPLEX PARTIAL SHADING CONDITIONS IN GRID CONNECTED ...
EXPANSION PLANNING WITH DG FOR POWER LOSSES REDUCTION NILESH CHOTHANI,ISHAN DESAI FOURIER TRANSFORM AND PROBABILISTIC NEURAL NETWORK BASED FAULT DETECTION IN DISTRIBUTION SYSTEM CONTAINING DGS P. ...
doi:10.1109/i-pact52855.2021.9696846
fatcat:x4os34tvsvb7hoxfvhprrkjdla
Intelligent Monitoring and Inspection of Power Line Components Powered by UAVs and Deep Learning
2019
IEEE Power and Energy Technology Systems Journal
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The results show that the proposed system is fast and accurate in detecting common faults on power line components, including missing top caps, cracks in poles and cross arms, woodpecker damage on poles ...
Finally, we propose the multi-stage component detection and classification based on the Single Shot Multibox detector and deep Residual Networks to detect small components and faults. ...
ACKNOWLEDGMENT The authors would like to thank eSmart Systems (Chi Hieu Huynh, Ngoc Hoang Tran, Dang Ha The Hien) and UiT Machine Learning Group (Michael Kampffmeyer) for support in the work with this ...
doi:10.1109/jpets.2018.2881429
fatcat:2d4oxlcvpnh2hicykzodaksqvq
Applied Machine Learning for IIoT and Smart Production—Methods to Improve Production Quality, Safety and Sustainability
2022
Sensors
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Furthermore, the boost in communication provided by IIoT requires special attention to increased levels of safety and security. ...
The growth in machine learning (ML) capabilities in the last few years has affected smart production in many ways. ...
Ref [77] uses convolutional networks to predict the error in timestamping based on the CIR of received packets, resulting in a one-order improvement in location accuracy on average compared to the geometric ...
doi:10.3390/s22239148
pmid:36501848
pmcid:PMC9739236
fatcat:c4n5bagqefagbmhk5yaxfctroa
Image Identification and Error Correction Method for Test Report Based on Deep Reinforcement Learning and IoT Platform in Smart Laboratory
2024
International Journal of Information Technologies and Systems Approach
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In order to solve the problems that most models are complex, time-consuming, and have difficulty in identifying image errors, an image identification and error correction method of test report based on ...
Then, the depth separable convolution improved convolutional neural network is used to extract image features, and the features are input into bidirectional recurrent neural networks (BiLSTM) for analysis ...
IMAGE RECoGNITIoN METHoD BASED oN DEEP LEARNING
Image Feature Extraction Based on Improved Convolutional Neural Network The deep information features of laboratory test report images need to be extracted ...
doi:10.4018/ijitsa.337797
fatcat:iiw4pkqikfcdlgv6vn7b7xlipi
Circuit Manufacturing Defect Detection Using VGG16 Convolutional Neural Networks
2022
Wireless Communications and Mobile Computing
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We use a convolutional neural network (CNN) with the Visual Geometry Group with 16 layers (VGG16) architecture and train it on the Printed Circuit Board (PCB) dataset with 3175 RBG images. ...
Manufacturing, one of the most valuable industries in the world, is boundlessly automatable yet still quite stuck in traditionally manual and slow processes. ...
This CNN model, on the other hand, can only identify splatter and delamination faults in metal LPBF. ...
doi:10.1155/2022/1070405
fatcat:mtxwqootnjeovkcpnear7oifia
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