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Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposed a particle swarm algorithm based on pyramid layer topology to optimize energy consumption trajectories of industrial robots. The algorithm introduced a pyramid layer topology to sort and stratify the particles thus improving the competitive strategy of the algorithm and increasing the population diversity. The algorithm introduced a new cooperation strategy to update the speed and position of the particles. It introduced a victory percentage to adaptively adjust the weight coefficients of the particle swarm algorithm and improved the search efficiency of the particles. In order to verify the effectiveness of the algorithm, this paper tested it on the set of test functions and compared it with other eight variants of particle swarm algorithms. The results show that the performance of the proposed algorithm has significant advantages. Finally, it applied the algorithm to industrial robot trajectory planning. Simulation experiments show that the algorithm can effectively solve the optimal trajectory of the robot's energy consumption, and the energy consumption of the robot is significantly reduced, which meets the kinematics and dynamics constraints of industrial robots. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Graph convolutional autoencoders emerged as powerful graph representation learning methods with promising performance on link prediction. However, existing methods typically rely on graph convolutional network to encode adjacency matrix and attribute matrix. This strategy ignores high-order features such as second-order information. This paper proposes a new SeVGAE model based on second-order graph convolutional autoencoders to tackle this problem. Firstly, graph convolutional network and second-order graph convolutional network are used to generate the mean and variance of the variational autoencoders. Then, the embeddings are learned to represent the mixed probability distribution of the original graph. Finally, the topology is recovered by the inner product decoder. SeVGAE performs better than the baselines in the link prediction. AUC and AP are raised by 3.26% and 2.56% respectively compared to the original VGAE on Citeseer dataset. The results show that the second-order information can retain richer graph information in low-dimensional embeddings. Besides, the proposed method has obvious advantages in insufficient attribute and inaccurate topology. In the extreme case where both edges and attributes are missing up to 40%, SeVGAE still improves AUC and AP by 4.79% and 3.47% respectively compared to VGAE. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Test & Measurement Technology is the property of Publishing Center of North University of China and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Surfactant Detergent & Cosmetics (2097-2806) is the property of China Surfactant Detergent & Cosmetics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The task of fraud detection in blockchain requires a thorough exploration of the inherent temporal and spatial characteristics in historical transaction data. Existing fraud detection methods suffer from large prediction errors. To address this issue, this paper proposed a blockchain fraud detection method, named RGCN-SRG, based on reinforced graph convolutional network (RGCN) and spatiotemporal recurrent gate (SRG). Firstly, leveraging Bitcoin's historical transaction data for the construction of the transaction graph, the method used a reinforced graph convolutional network with different kernel sizes to comprehensively extract the graph's topology information and generate feature vectors. Additionally, considering the temporal characteristics of blockchain transactions, the method introduced a spatiotemporal recurrent gate structure that incorporated graph convolutional operations into the traditional gate structure to extract dependency information from multiple spatiotemporal dimensions of the transaction graph. Finally, it obtained the prediction results of money laundering detection through a linear layer and activation function. The proposed fraud detection method was evaluated by the constructed dataset. Compared with GCN, DEDGAT, EGT and GCN + MLP F, by the proposed method improves 18.4, 10.7, 9.2 and 4.9 percentage points, respectively; the precision improves 11.5, 11.2, 7.7 and 3.7 percentage points, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of New Architecture is the property of New Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The adaptive motion algorithm based on predetermined motion trajectories is studied in this paper, addressing the problem of vehicle formation with multiple sensors. Firstly, optimal da- ta fusion estimation of sensor data from multiple sensors was obtained through processing using Kalman filtering acquiring the optimal position information of the vehicle formation. Then, the next step of vehicle formation motion planning was obtained through the exchange of position es- timation information between vehicles. Two types of vehicle formation motion were considered: fixed bidirectional communication cluster movement without a leader vehicle and fixed unidirec- tional communication cluster movement with a leader vehicle. The proposed method, unlike situa- tions where only the movement of formation vehicles towards the destination was controlled.ena- bled the vehicle formation to move towards the endpoint along the predetermined trajectory through the exchange of position information between adjacent vehicle nodes. To meet the practi- cal requirement of maintaining an ideal distance between vehicles, two virtual force models, name- ly traction force and topological force were introduced. Traction force primarily guides vehicles a- long the predetermined path to reach the destination, while topological force mainly maintains the connection topology among following vehicles. Simulation results indicate that the proposed method.compared to existing methods. effectively shortens the safe distance between vehicles and improves road utilization efficiency.demonstrating the good applicability. [ABSTRACT FROM AUTHOR]

How to enhance system consensus is an important problem in the research of multi agent systems. The conventional consensus protocols usually does not consider the Hub Nodes in the topology, and the topology weight was single, which made the system easier to split. Based on the idea that key figures in the interpersonal network could promote information exchange in different communities, this paper proposed an influence network model（INM）. First, this paper proposed a Distributed Hub Node Identify algorithm（ DHNI） to distinguish between Hub Nodes and Non Hub Nodes. Distributed multi-agent system could apply DHNI. Secondly, this paper proposed a distributed Hub Node based topology reweighting algorithm （DHNTR） to quantify the influence of different nodes on their neighbors. Finally, this paper proposed an influence network-based multi-agent consensus protocol. this paper designed a common Lyapunov function and analyzed the global stability of the system. this paper proved the stability of the system in the sense of Lyapunov. Simulation results show that the protocol can enhance system consensus. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High-quality community detection for large-scale complex networks usually depends on the topology of the graph, which used to divide the node set. However, real-world networks usually have noisy and cluster-independent links, which may cause the model to divide the nodes from different clusters together. This paper proposed a algorithm called graph reconstruction based community detection (GRCD). This method could handle community detection in large-scale complex networks. GRCD firstly deleted the connected edges between communities to reconstruct the community structure of the original graph. Subsequently, GRCD regarded the network as a social system, aiming to reveal the community in a more intuitive way. This paper proposed an efficient community detection strategy : a community organization generation strategy based on discourse power. Extensive experiments were performed on datasets of different sizes. The results show that GRCD can not only deal with large-scale networks, but also has strong competitiveness in the quality of its community division compared with several existing benchmark algorithms while maintaining high stability. [ABSTRACT FROM AUTHOR]

Consensus algorithm based on credit has significant advantages in consensus efficiency and security, which has received great attention from academy and industry in recent years. This paper made a comparative analysis of the current consensus algorithms based on credit to provide reference for researchers to study in depth. Firstly, this paper systematically reviewed the state-of-the-art consensus algorithms based on credit, gave its development history, classification and core working principle, and summarized its credit calculation model and performance evaluation indicators. Secondly, it analyzed the creditbased consensus algorithms qualitatively and quantitatively, and pointed out their advantages and disadvantages. Finally, aiming at the problems of insufficient credit incentive and low integration with the consensus process in the state-of-the-art consensus algorithms, this paper proposed to optimize from the credit incentive based on game theory and designing efficient communication topology, and gave the future research direction. [ABSTRACT FROM AUTHOR]

In the Walras-Cassel type general equilibrium system, the coincidence of the number of equations and the number of unknown variables was regarded as the existence condition of the equilibrium solution. On the other hand, Wald, Schlesinger, von Neumann and others have investigated the mathematical conditions ensuring the existence of equilibrium solutions, especially focusing on a non-negative solution. Also, with the advent of Brauwer and Kakutani's fixed point theorem, the discussions for the existence of competitive equilibrium solutions were brilliantly developed by applying topology. With the theme of general equilibrium analysis, this paper traces the historical lineage of theories surrounding the conditions for the existence of competitive equilibrium solutions, focusing mainly on the mathematical content of analytical tools, and attempts to give an overview of them. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the current hand pose estimation which doesn’t fully use 2D information to assistance 3D hand mesh reconstruction, this paper further introduced HOG feature of the RGB image based on the use of hand Mask and 2D heatmaps. This paper designed the framework of multi task learning CNN to extract the 2D information, and used the topology of the hand to fused the relevant information. In order to solve two problems: the consistency of hidden Embeddings dimensions in Transformer Encoder as well as requires heavy computational resources, the model introduced a new MLP (Multi-Layer Perception) module into transformer encoder to increase the length of Embeddings and decrease the dimensions of Embeddings, thereby the hand Mesh was completed in the way from coarse to fine. The new method proposed in this paper has achieves better results in two Frei-HAND and RHD datasets. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aimed at the problems that the multi-workstation revolver of ultra high-speed packaging machine had high motion inertia impact and high structure dynamic characteristics under the condition of large dead weight, ultra high-speed rotation and complex multi-workstation load. The paper analyzed the working load and constraint condition of multi-workstation revolver under rated working condition, and the finite element analysis model was constructed by using ANSYS Workbench platform, and the optimal topology optimization material distribution characteristics of multi-workstation revolver in the design domain was calculated with topology optimization technology, and based on the topology optimization density map and 3D model, two optimized schemes were constructed by the structure scheme of gradient ring band and stiffener and the structure scheme of gradient arc groove and weight reduction hole respectively with symmetric structure. The results showed that the structure scheme of gradient ring band and stiffener is optimal, which can be meet the static and structural natural frequency requirements under proper working load at the same time, compared with the prototype design, the quality of the optimal structure scheme is reduced by 16. 33%, and the maximum equivalent stress of the optimal structure scheme is reduced by 11.25%, and the dynamic specific stiffness efficiency of the optimal structure scheme is increased by 4.14%. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The shortest path tour problem(SPTP) aims to determine the shortest path between two nodes. In addition, the path must pass through multiple disjoint node subsets in a given order. This paper proposed the specific decomposition method for the ripple-spreading algorithm(RSA) to solve the SPTP. The RSA simulates ripple propagation patterns on the water surface and establishes connections among subproblems, which reduces computational redundancy compared to other decomposition methods. This paper adapted the RSA to make it solve the SPTP with multiple sources and destinations while maintaining time complexity. Comparative experiments on various network topologies show that the RSA ensures optimality and outperforms other algorithms in computational efficiency. The efficiency of the RSA when solving the SPTP with multiple sources and destinations makes it can provide solutions to real-world problems efficiently and demonstrates its application values. [ABSTRACT FROM AUTHOR]

In recent years, the application of drones has become more and more common, and multiple drones can work together to complete tasks, which greatly improves work efficiency. Based on this phenomenon, many scholars devote themselves to the research on the communication mode of UAV swarms, and routing protocols are always the focus of network research. Aiming at the problem that the routing metric selected in the research of routing protocols in the existing literature fails to combine the performance level of the UAV self-organizing network at that time and results in unreasonable routing decisions, this paper proposed a multi-indicator and multi-path optimized link state routing protocol with load awareness and network topology change awareness（Optimized Link State Routing Protocol based on Multi-indicators and Multi-Path, MIMP-OLSR）. Firstly, the proposed protocol considered the mobility characteristics of nodes and the lifetime of the network in the UAV scene, and defined three indicators for routing, namely the node’s MAC layer blocking degree, the node’s neighbor change rate and the number of MPR＿S neighbors of the node; Secondly, combined with HELLO and TC control messages, this paper proposed an indicator notification mechanism to flood the indicator information to the whole nodes of the network; Finally, according to the indicator information, this paper proposed a multi-path routing scheme. The Simulation results show that compared with OLSR, SETT＿MPOLSR and UAV-OLSR protocols, the proposed MIMP-OLSR protocol significantly improves success rate, end-to-end delay and throughput performance, which further proves the rationality of the proposed multipath routing scheme. [ABSTRACT FROM AUTHOR]

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the data plane configuration problem caused by overlapping forwarding paths of different applications in SDN network, this paper proposes a Boolean function-based network reachability verification method. First, it abstracts the network topology into port topology and calculates the port adjacency matrix; then generates the path space of the network and the forwarding function of each port, and calculates the path function of each path; finally, it judges the accessibility of path from the satisfiability of path function. Through simulation experiments, this paper studies the influence of factors such as network topology and flow rule scale on the algorithm verification efficiency, and the performance of the proposed method is compared with APV and DASDA. Experimental results show that the proposed method can effectively detect flow rule configuration problems in SDN networks. As the number of loops in the network increases and the size of the flow rules grows, the time overhead required to verify the network gradually increases. Among them, the network topology has a great influence on the path generation time, and the generation time of the forwarding function is mainly affected by the scale of the flow rule. Compared with APV and DASDA, the time to verify is shortened by an average of about 53.76% and 27.74%, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Most existing text classification algorithms based on graph neural network ignore the problem of over-smoothing, and ignore the problem of information loss due to graph topology, resulting in poor classification performance. To solve this problem, this paper proposed a method to measure the smoothness of multiple text graph representations WACD and a regularization term RWACD to suppress over-smoothing. Subsequently, this paper proposed an attention and residual-based network structure ARS to compensate for the loss of textual information due to graph topology differences. Finally, this paper proposed a graph convolutional neural network text classification algorithm RA-GCN. RA-GCN used ARS to fuse text representations in the graph representation learning layer, and used RWACD in the readout layer to suppress over-smoothing. This paper conducted experiments on 6 Chinese and English datasets. The experimental results demonstrate the classification performance of RA-GCN, and the effects of RWACD and ARS are verified through multiple comparative experiments. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Human understanding of things is often from coarse to fine and then to refined. Inspired by the cognitive process, this paper proposed a new gesture estimation network structure based on hand topology. Firstly, this model extracted the global feature from the angle of the whole hand, then extracted the local feature from the angle of the finger, finally extracted the refined feature from the angle of the joint point, and regressed the 3 D spatial coordinate information of each joint point by fusing the different features of the three stages. Since the depth map only saved the depth information from the target point to the camera, taking the depth map as the input of the neural network, the convolution kernel couldn't directly obtain the coordinate information in the other two directions. In order to obtain the coordinate information of the other two directions, it converted the depth map into a 3-channel image using the camera imaging principle, which improved the regression accuracy of the neural network. This paper trained and tested the model on the NYU and MSARA datasets. The test results show that the proposed network structure and the transformation of the input data have achieved good results. [ABSTRACT FROM AUTHOR]

Recently, graph neural networks have received widespread attention due to their rich representation and reasoning capabilities. To best knowledge, current research mainly focuses on amending the convolutional strategy and network structure for higher performance, so the performance will be inevitably constrained by the limitations of the single model. Inspired by the idea of ​​ensemble learning, this paper innovatively proposed an ensemble learning framework for graph neural network (EL-GNN).Unlike regular text and images, graph data not only had features but also had rich topology information. Therefore, EL -GNN additionally supplemented the structure information during the ensemble stage rather than merely integrating the prediction results of independent classifiers. Besides, this paper further revised the ensemble strategy through reconstructing a feature-level similarity graph for subsequent assembling, which balances the feature and structure information on the basis of the assumptions of those nodes with the similar feature or easy reachability of high probability to share the same labels .The comprehensive experiments indicate that the proposed ensemble strategy achieves an impressive performance and EL-GNN is superior to other off-the-shelf models on the node classification task. The comprehensive experiments indicate that the proposed ensemble strategy achieves an impressive performance and EL-GNN is superior to other off-the-shelf models on the node classification task. The comprehensive experiments indicate that the proposed ensemble strategy achieves an impressive performance and EL-GNN is superior to other off-the-shelf models on the node classification task. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The UAV Ad hoc network receives extensive attention in recent years due to its strong anti-interference ability, suitable for complex terrain, high degree of intelligence and low cost. The design and optimization of the routing protocol in this network are always the core research problem. Aiming at the problem that the node doesn't update the local route in time due to it's rapid movement in the UAV Ad hoc network, this paper proposed a dynamic sensor optimized link state routing protocol based on the Q-learning algorithm (dynamic sensor optimized link state routing based on Q-learning algorithm, DSQ-OLSR). Firstly, the proposed protocol fully considered the characteristics of the high-speed movement of nodes in the UAV Ad hoc network. When selected MPR (multi-point relay) nodes, this paper added two indicators of link stability and link existence time to make the selected MPR nodes set more stable and reasonable. In addition, this paper used the Q-learning algorithm to adjust the sending interval of TC messages adaptively. In order to reduce control overhead, the proposed algorithm increased the TC sending interval when the network topology changed slightly. In order to meet the requirements of rapid perception and construction of the network topology and further realize the timely routing of data, the algorithm reduced the TC sending interval when the topology changed greatly. The simulation results show that compared with the DT-OLSR (dynamic topology link state routing based on Q-learning algorithm) protocol, the proposed protocol improves the end-to-end delay, throughput, success rate and network lifetime performance by 12. 6 1%, 9. 28%, 7. 69% and 5. 86% respectively, which verifies the effectiveness of this protocol. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem of maximizing the network coverage a rea of the directed vision sensor network while maintaining connectivity of the network topology, this paper proposed the strategy of connectivity and cove rage control of sensor networks equipped with fisheye lenses. Firstly, this paper established the mathematical model and coverage performance function of a single directed vision sensor. Then, it determined the chain connection maintenance strategy. The strategy determined the direction of movement by comparing the coverage strength of the left and right sides of the node H1 (z) and Hr (z), so that the network spread outward. Then through the controller, the rotation angle of the node was restricted not to exceed the maximum rotation angle Δθi,j, and the movement step length did not go out of the field of view radius Rs of the link point N..i. Therefore, it ensured the connectivity of the entire network. Finally, the simulation results show that the control strategy can maximize the coverage a rea of the sensor network and always maintain the connectivity of the network topology, which shows the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the existing graph auto-encoders can't capture the context information between nodes of the graph, this paper proposed adaptive graph auto-encoder based on restarted random walk. It firstly constructed a two-layer graph convolutional network to encode the topology and features of the graph. At the same time, it carried out the restarted random walk to capture the context information between nodes. Next, it designed the adaptive learning strategy to aggregate the representations obtained by restarted random walk and graph convolutional network. It can adaptively assign weights according to the importance of the two representations. To prove the effectiveness of the proposed method, this paper applied the final representations of the graph to the task of node clustering and link prediction. The experimental results show that the proposed method achieves more advanced performance compared with the baseline methods. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The method of market mechanism is rigorous in mathematical derivation, clear in theoretical explanation, small in algorithm computation, and less limited in network scale and topology structure. This paper reviewed the classical li-terature and recent studies about two methods based on market mechanism; auction and contract net, and introduced and summarized the basic principle, progress, application background and limitations of this method in detail. Finally, the summary presented the key issues and future research trends in the research of task allocation for unmanned swarm based on market mechanism. [ABSTRACT FROM AUTHOR]

How to deal with network faults efficiently and quickly is the basic requirement and main task of designing routing protocol. When dynamic routing protocols deal with network faults, a large number of packets are discarded during dynamic convergence. Therefore, at present, router manufacturers generally use routing protection methods to overcome network failures. Among many route protection methods, the DC (downstream criterion) rules is a generally recognized method. However, the time complexity of the existing DC rules algorithms is generally high, and the complexity increases rapidly with the increase of the average degree of network nodes. In order to deal with the above problems, this paper proposed a linear time complexity university routing protection scheme ERPLR (efficient routing protection method with linear time complexity). The method firstly proposed the backup next hop calculation rule, and then calculated the backup next hop for all source-destination node pairs based on the existing shortest path tree according to the backup next hop calculation rule. In the process of calculating the backup next hop, accessing each node and its neighbors at most once, so the time complexity of ERPLR is O（V+E). The experimental results show that, compared with the existing rules for implementing DC rules, ERPLR has similar results in four metrics: failure protection ratio and path stretch. Compared with DC rules, ERPLR reduces the computational overhead by about 74.93% and 78.91% in real topology and generated topology, respectively, this method can greatly reduce the calculation cost of DC rules. [ABSTRACT FROM AUTHOR]

As the growth of social network scale, so do challenges to the existing anomaly detection algorithms. Therefore, this paper proposed an anomaly detection method based on graph modularity clustering（GMC＿AD）, which could be applied to solve the problem of low detection efficiency caused by network size and complexity. Based on analyzing the network topology structure, the GMC＿AD method improved the efficiency of events detection by weighting mechanism on abnormal nodes and modularity clustering algorithm. The GMC＿AD processes could be described as follow: a)Since designing a quantization strategy for node evolution in the network, GMC＿AD get the set of abnormal nodes by recognizing nodes with abnormal evolutionary behaviors. b)The method used a modularity clustering algorithm to reduce the network size. c)During the calculation of network fluctuation value, it introduced a weighting mechanism for taking the influence of abnormal nodes into consideration, after that, the GMC＿AD method detected the abnormality by the changes of network fluctuation value. On real social network datasets VAST, EU＿E-mail and ENRON, the GMC＿AD method accurately detected the abnormal periods. The event detection sensibility of GMC＿AD method was increased by 50%～82% meanwhile the run-time efficiency increased by 30%～70%. The GMC＿AD method enhances not only the accuracy and sensitivity but also the efficiency of anomaly detections. [ABSTRACT FROM AUTHOR]

Ningbo urban-rural fringe areas,selected for the rail transit node and conventional public traffic adaptive connection problem,considering the average daily full are theory-oriented,line passenger capacity,line network repetitive,passenger load factor and other constraints,this paper used ARCGIS software powerful storage and computing power,good ability of superposition of line network,and optimized the network topology node nonstop passenger flow detection analysis,and based on the Ningbo urban and rural integration of traffic planning and construction background,explored the Ningbo urban and rural integration of rail transit and theory-oriented and coordinate the relationship between optimization and the connection of the two forms.This paper studied the coordination and optimization mechanism of the traffic network of the urban and rural fringe of Ningbo in the aspects of station and network operation by using the accessibility method and the shortest route marking method comprehensively.Furthermore,it visualized the optimization results of rail transit network connecting Ningbo urban and rural areas.The experimental results show that the optimized traffic line network in the urban and rural fringe of Ningbo city is superior to the current strategy.This research model scheduling strategy can provide a reliable optimization scheme for the traffic control department of the urban and rural fringe of Ningbo city,and provides a scientific basis for the urban-rural fringe of other cities to make a correct traffic control policy. [ABSTRACT FROM AUTHOR]

Aiming at the dynamic changes of network topology of UAV group in the complex environment of military confrontation, this paper proposed a lightweight dynamic key management scheme for UAV group, which solved the key update problems when the network topology changed dynamically, such as UAV joining and exiting, batch joining and exiting, group merging and splitting. When the network topology didn't change, the scheme could also provide local periodic key update to improve the efficiency of UAV group key update. By constructing a congruent system, the scheme divided the secret information into user space, free space and retract space, the user space could calculate and recover the session group key after receiving the broadcast message from KGM, but the free space and retract space couldn't calculate and recover the group key. During the key update process, KGM used idle time to select the key from the key pool in advance for predictive calculation, which reduced the delay caused by constructing broadcast messages for complex calculation. Through analysis and experiments, the scheme has forward and backward security, anti-collusion attack and node cancellation capabilities. Compared with existing UAV key management schemes, the scheme optimizes the computation and communication overhead, and the node storage overhead is small, which is suitable for the UAV group network with dynamic topological changes. [ABSTRACT FROM AUTHOR]