Weighted Self-regulation Complex Network-Based Modeling and Key Nodes Identification of Multistage Assembling Process

Through digging out the core suppliers and core customers from the numerous suppliers and customers in the complex network of E-commerce, it contributes to reducing the adverse selection for the consumers and moral hazards for the operators caused by information asymmetry. Meanwhile, it is very meaningful for the credit risk protection in the complex network of E-commerce. On the basis of the references to the White and Smyth algorithms, in this paper, improvements from the White and Smyth algorithms are made herein, combining several features of the E-commerce complex network such as competitiveness, incomplete information and unsymmetrical information. In addition, an algorithm for mining the key nodes in E-commerce complex network is put forward, and applications are explained by instances.

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Identification of Key Nodes in Aircraft State Network Based on Complex Network Theory

IEEE Access ◽

10.1109/access.2019.2915508 ◽

2019 ◽

Vol 7 ◽

pp. 60957-60967 ◽

Cited By ~ 5

Author(s):

Wang Zekun ◽

Wen Xiangxi ◽

Wu Minggong

Keyword(s):

Complex Network ◽

Network Theory ◽

Complex Network Theory ◽

Key Nodes

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Cooperative Multi-UAV Collision Avoidance Based on a Complex Network

Applied Sciences ◽

10.3390/app9193943 ◽

2019 ◽

Vol 9 (19) ◽

pp. 3943 ◽

Cited By ~ 1

Author(s):

Huang ◽

Tang ◽

Lao

Keyword(s):

Conflict Resolution ◽

Collision Avoidance ◽

Complex Network ◽

Computing Time ◽

Real Life ◽

Traffic Density ◽

Contraction Method ◽

Cn Algorithm ◽

Multi Uav ◽

Key Nodes

The conflict resolution problem in cooperative unmanned aerial vehicle (UAV) clusters sharing a three-dimensional airspace with increasing air traffic density is very important. This paper innovatively solves this problem by employing the complex network (CN) algorithm. The proposed approach allows a UAV to perform only one maneuver—that of the flight level change. The novel UAV conflict resolution is divided into two steps, corresponding to the key node selection (KS) algorithm based on the node contraction method and the sense selection (SS) algorithm based on an objective function. The efficiency of the cooperative multi-UAV collision avoidance (CA) system improved a lot due to the simple two-step collision avoidance logic. The paper compares the difference between random selection and the use of the node contraction method to select key nodes. Experiments showed that using the node contraction method to select key nodes can make the collision avoidance effect of UAVs better. The CA maneuver was validated with quantitative simulation experiments, demonstrating advantages such as minimal cost when considering the robustness of the global traffic situation, as well as significant real-time and high efficiency. The CN algorithm requires a relatively small computing time that renders the approach highly suitable for solving real-life operational situations.

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A New Evaluation Method of Node Importance in Directed Weighted Complex Networks

Journal of Systems Science and Information ◽

10.21078/jssi-2017-367-09 ◽

2017 ◽

Vol 5 (4) ◽

pp. 367-375 ◽

Cited By ~ 1

Author(s):

Yu Wang ◽

Jinli Guo ◽

Han Liu

Keyword(s):

Complex Networks ◽

Complex Network ◽

Real World ◽

Evaluation Method ◽

Network Models ◽

Node Importance ◽

Weighted Complex Network ◽

Complex Network Models ◽

Evaluation Matrix ◽

Key Nodes

AbstractCurrent researches on node importance evaluation mainly focus on undirected and unweighted networks, which fail to reflect the real world in a comprehensive and objective way. Based on directed weighted complex network models, the paper introduces the concept of in-weight intensity of nodes and thereby presents a new method to identify key nodes by using an importance evaluation matrix. The method not only considers the direction and weight of edges, but also takes into account the position importance of nodes and the importance contributions of adjacent nodes. Finally, the paper applies the algorithm to a microblog-forwarding network composed of 34 users, then compares the evaluation results with traditional methods. The experiment shows that the method proposed can effectively evaluate the node importance in directed weighted networks.

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Mathematical Model Construction of the Production Workshop Based on the Complex Network and Markov Theory

Mathematical Problems in Engineering ◽

10.1155/2021/1912442 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Gang Guo ◽

Fengjing Shao

Keyword(s):

Prediction Model ◽

Production Process ◽

Complex Network ◽

Network Theory ◽

Dynamics Model ◽

Complex Network Theory ◽

Simulation Results ◽

Markov Method ◽

Key Nodes ◽

Good Agreement

Because of the advantages of the complex network in describing the interaction between nodes, the complex network theory is introduced into the production process of the modern workshop in this paper. According to the characteristics of the workshop, based on extracted key nodes, the complex network model of the workshop is constructed to realize the mathematical description of the production process of the workshop. Aiming at the multidisturbance factors in the production process of the workshop, the key disturbance factors are predicted based on the Markov method, and the propagation dynamics model close to the actual production of the workshop is established. Finally, the bottleneck prediction model of the workshop under the disturbance environment is established. The simulation results show that the proposed prediction model is in good agreement with the actual data, and the coincidence rate is as high as 93.7%.

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