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A Double-Layer Combination Algorithm for Real-Time Information-Sharing Network Design Problem
2021
Complexity
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This paper designs a low-carbon model and focuses on the real-time information-sharing network in order to get sustainable strategies promptly and exactly. ...
Firstly, the biobjective information-sharing network model is established to describe real-time problem with total cost and carbon emission factor. ...
e Design Ideas of Double-Layer Combination Algorithm. ...
doi:10.1155/2021/4856593
doaj:85385fc66b7040bba9254f5e5651f024
fatcat:hchcfp7jabb7zgjldmr7phbrmm
Parallel Ensemble Deep Learning for Real-Time Remote Sensing Video Multi-Target Detection
2021
Remote Sensing
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It combines a deep learning target detection algorithm with template matching to make full use of image information. ...
At the same time, the real-time and stable display of detection results is realized by aiming at the moving UAV video image. ...
Acknowledgments: We would like to express our heartfelt thanks to anonymous reviewers and editors for their constructive comments on the paper. ...
doi:10.3390/rs13214377
fatcat:ddjwhsx5urgplgkktc6rfnpg4e
The Past, Present, and Future of Transport-Layer Multipath
[article]
2016
arXiv
pre-print
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Since congestion control defines a fundamental feature of the transport layer, we study the working of multipath rate control and analyze its stability and convergence. ...
scheduling mechanisms for use with multiple paths. ...
The application layer and the transport layer can work together to design better protocols for real-time applications while the interaction between the transport layer and the network layer is simultaneously ...
arXiv:1601.06043v1
fatcat:5hzuk53f55fghmf6k53wvcsfx4
Theoretical Research on the Time Delay and Corresponding Issues for the Novel Category of Internet of Things Control System
2016
International Journal of Future Generation Communication and Networking
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of things have the effect of information transmission, the layer is mainly used for the data transfer between perception layer and application layer and it is a bridge connecting the perception layer ...
Sharing network inevitably the introduction of network time delay, in most cases they are incident or random [26] . ...
Acknowledgements This work was financially supported by the 2013 Research Fund Project of Xijing University.Project name: Research on real time monitoring system of surface subsidence based on GPS and ...
doi:10.14257/ijfgcn.2016.9.10.01
fatcat:xkykjy5f5vaohchbtfrizktgrq
A Cross-camera Multi-face Tracking System Based on Double Triplet Networks
2021
IEEE Access
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Double Triplet Networks (DTN) designed in this study is used to learn the depth features of human face. ...
Cross-camera face tracking is possible by transmitting facial features between cameras in real-time. ...
SYSTEM DESIGN This paper proposes an improved DTN (Double Triplet Networks, DTN) for real-time multi-face tracking in multi camera field of view. ...
doi:10.1109/access.2021.3061572
fatcat:2zi3ga3ilvdp5lrnwqew65r6ai
Feature Importance-aware Graph Attention Network and Dueling Double Deep Q-Network Combined Approach for Critical Node Detection Problems
[article]
2021
arXiv
pre-print
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This work proposes a feature importance-aware graph attention network for node representation and combines it with dueling double deep Q-network to create an end-to-end algorithm to solve CNP for the first ...
A Critical Node Problem (CNP) aims to find a set of critical nodes from a network whose deletion maximally degrades the pairwise connectivity of the residual network. ...
Conclusion This work presents FGDD as a new DRL-based algorithm for a critical node problem that generalizes well to unseen networks size and structures. ...
arXiv:2112.03404v1
fatcat:h5lnx2qcfvaqbgk76cosx6w3gy
A Vehicle Reidentification Algorithm Based on Double-Channel Symmetrical CNN
2021
Advances in Multimedia
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In order to solve the above problems, a double-channel symmetric CNN vehicle recognition algorithm is proposed by improving the network structure. ...
In this method, two samples are taken as input at the same time, in which each sample has complementary characteristics. ...
At the same time, the recognition rate will be improved because the double-channel CNN network can input more features. is study attempts to design a double-channel symmetrical CNN structure for vehicle ...
doi:10.1155/2021/8899007
fatcat:kujnnm3ocjah3f75iod47lnedu
Applications of Artificial Intelligence in Transport: An Overview
2019
Sustainability
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Moreover, it is promising for transport authorities to determine the way to use these technologies to create a rapid improvement in relieving congestion, making travel time more reliable to their customers ...
Examples of AI methods that are finding their way to the transport field include Artificial Neural Networks (ANN), Genetic algorithms (GA), Simulated Annealing (SA), Artificial Immune system (AIS), Ant ...
Designing an optimal road method for transport planning is part of the Network Design Problem (NDP) [56] . ...
doi:10.3390/su11010189
fatcat:d25yx4iuzbd7hfrnhmjag7jzxq
Bandwidth Allocation Scheduling Algorithms for IEEE 802. 16 WiMax Protocol to Improve QoS: A Survey
2014
International Journal of Computer Applications
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This paper evaluates and compare various existing algorithms and enlighten different issues in designing of these algorithms, furthermore a new bandwidth allocation scheduling algorithm is proposed for ...
In recent times, wireless network is extensively accessed technology to connect remote user terminal with its primary network. ...
This algorithm cannot be used for mobile networks because it does not give fair bandwidth and QoS for these networks [8] .To solve this problem, a scheduling algorithm [10] that combines CSDPS with ...
doi:10.5120/17227-7550
fatcat:pyyzdkekqjdt3n5zvzw7gr4tfu
Task Offloading Based on LSTM Prediction and Deep Reinforcement Learning for Efficient Edge Computing in IoT
2022
Future Internet
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To reduce the cost of resources required for task offloading and improve the utilization of server resources, in this paper, we model the task offloading problem as a joint decision making problem for ...
In the training phase of the model, this algorithm predicts the load of the edge server in real-time with the LSTM algorithm, which effectively improves the convergence accuracy and convergence speed of ...
The algorithm combines Long Short-Term Memory (LSTM) and deep reinforcement learning (DRL) to predict task dynamic information in real-time, based on the observed edge network condition and the server ...
doi:10.3390/fi14020030
fatcat:qygvajrhivatlpkm77gq6py6ri
Generating 3D texture models of vessel pipes using 2D texture transferred by object recognition☆
2021
Journal of Computational Design and Engineering
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Therefore, this study investigates an improved CycleGAN algorithm that can be specifically applied to the shipbuilding industry by combining a modified object-recognition algorithm with a double normalization ...
However, when applying CycleGAN's textures to pipe structures, the performance is insufficient for direct application to industrial piping networks. ...
Double normalization The internal covariate shift problem, in which the input distribution of each layer of the network varies as the layer of the model becomes deeper, also occurs. ...
doi:10.1093/jcde/qwaa090
fatcat:roiwxngwrnetvnz4bmg5sscnu4
Double Ghost Convolution Attention Mechanism Network: A Framework for Hyperspectral Reconstruction of a Single RGB Image
2021
Sensors
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In this study, we propose the double ghost convolution attention mechanism network (DGCAMN) framework for the reconstruction of a single RGB image to improve the accuracy of spectral reconstruction and ...
The proposed DGCAMN consists of a double ghost residual attention block (DGRAB) module and optimal nonlocal block (ONB). ...
The shared perception layer share multilayer perceptron (MLP) contains a hidden layer for the size of the vector (r is the reduction ratio). ...
doi:10.3390/s21020666
pmid:33477959
fatcat:lg3t3w66aveh5e5vge3ghscwzq
Multipath Transmission for the Internet: A Survey
2016
IEEE Communications Surveys and Tutorials
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, application and cross layers; (2) we survey the state-of-the-art for each layer, investigate the problems that each layer aims to address, and make comprehensive assessment of the solutions; (3) based ...
To that end, we present a survey on multipath transmission and make several major contributions: (1) we present a complete taxonomy pertaining to multipath transmission, including link, network, transport ...
[27] presented a network layer architecture to aggregate bandwidth on multiple paths for real-time applications. ...
doi:10.1109/comst.2016.2586112
fatcat:vnpjtjx2dzfobbtzan5l6nnx7y
Learning Feature Fusion in Deep Learning-Based Object Detector
2020
Journal of Engineering
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The present work shows a qualitative approach to identify the best layer for fusion and design steps for feeding in the additional feature sets in convolutional network-based detectors. ...
Object detection in real images is a challenging problem in computer vision. ...
However, deep learning networks are designed for specific input sizes which pose a challenge for algorithm designer to feed in extra information in the network unless the network is redesigned. e work ...
doi:10.1155/2020/7286187
fatcat:6heao53bpnhahbvgb6p7ffb3l4
A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids
2019
Energies
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preferences and response to real-time market conditions. ...
In this paper, we investigate the potential of applying a Q-learning algorithm into a continuous double auction mechanism. ...
Due to the uncertainty and complexity of price intersections, a layering method and a price-prioritized quantity-weighted sharing rule are combined to solve the energy sharing problem. ...
doi:10.3390/en12152891
fatcat:z3adfrb7ivgiljavsm7puxsbie
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