Research on the Space-Based Integrated Information Network Evolution Model Visualization Methods Based on the Super Network Theory

2017 ◽  
Author(s):  
Chengxiang Liu ◽  
Wei Xiong
Keyword(s):  
Network Theory ◽  
Network Evolution ◽  
Evolution Model ◽  
Information Network ◽  
Model Visualization ◽  
Integrated Information

scholarly journals Dynamic Evolution Model of a Collaborative Innovation Network from the Resource Perspective and an Application Considering Different Government Behaviors

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 138 ◽  
Author(s):  
Wu ◽  
Shao ◽  
Feng
Keyword(s):  
Network Evolution ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Innovation Network ◽  
Transfer Policy ◽  
Collaborative Innovation ◽  
Innovation Output ◽  
The Government ◽  
Small Change ◽  
Innovative Behaviors

The evolution of a collaborative innovation network depends on the interrelationships among the innovation subjects. Every single small change affects the network topology, which leads to different evolution results. A logical relationship exists between network evolution and innovative behaviors. An accurate understanding of the characteristics of the network structure can help the innovative subjects to adopt appropriate innovative behaviors. This paper summarizes the three characteristics of collaborative innovation networks, knowledge transfer, policy environment, and periodic cooperation, and it establishes a dynamic evolution model for a resource-priority connection mechanism based on innovation resource theory. The network subjects are not randomly testing all of the potential partners, but have a strong tendency to, which is, innovation resource. The evolution process of a collaborative innovation network is simulated with three different government behaviors as experimental objects. The evolution results show that the government should adopt the policy of supporting the enterprises that recently entered the network, which can maintain the innovation vitality of the network and benefit the innovation output. The results of this study also provide a reference for decision-making by the government and enterprises.

A continuous-time network evolution model describing 3-interactions

2021 ◽  
pp. 1-20
Author(s):  
István Fazekas ◽  
Attila Barta ◽  
Csaba Noszály ◽  
Bettina Porvázsnyik
Keyword(s):  
Continuous Time ◽  
Network Evolution ◽  
Evolution Model

A transportation network evolution model based on link prediction

2021 ◽  
Author(s):  
Shuang Gu ◽  
Keping Li ◽  
Yan Liang ◽  
Dongyang Yan
Keyword(s):  
Network Structure ◽  
Link Prediction ◽  
Transportation Networks ◽  
Network Evolution ◽  
Evolution Model ◽  
Civil Aviation ◽  
Node Degree ◽  
Network Efficiency ◽  
Evolution Mechanism ◽  
Proposed Model

An effective and reliable evolution model can provide strong support for the planning and design of transportation networks. As a network evolution mechanism, link prediction plays an important role in the expansion of transportation networks. Most of the previous algorithms mainly took node degree or common neighbors into account in calculating link probability between two nodes, and the structure characteristics which can enhance global network efficiency are rarely considered. To address these issues, we propose a new evolution mechanism of transportation networks from the aspect of link prediction. Specifically, node degree, distance, path, expected network structure, relevance, population and GDP are comprehensively considered according to the characteristics and requirements of the transportation networks. Numerical experiments are done with China’s high-speed railway network, China’s highway network and China’s inland civil aviation network. We compare receiver operating characteristic curve and network efficiency in different models and explore the degree and hubs of networks generated by the proposed model. The results show that the proposed model has better prediction performance and can effectively optimize the network structure compared with other baseline link prediction methods.

A Physarum Network Evolution Model Based on IBTM

2013 ◽  
pp. 19-26 ◽  
Author(s):  
Yuxin Liu ◽  
Zili Zhang ◽  
Chao Gao ◽  
Yuheng Wu ◽  
Tao Qian
Keyword(s):  
Network Evolution ◽  
Evolution Model ◽  
Model Based

scholarly journals The evolution of political networks: Evidence from the Council of the European Union

2017 ◽  
Vol 19 (1) ◽  
pp. 25-51 ◽  
Author(s):  
Narisong Huhe ◽  
Daniel Naurin ◽  
Robert Thomson
Keyword(s):  
Decision Making ◽  
European Union ◽  
Network Theory ◽  
Network Evolution ◽  
The European Union ◽  
Unique Combination ◽  
Policy Positions ◽  
Political Actors ◽  
Political Networks ◽  
Over Time

We test two of the main explanations of the formation of political ties. The first states that political actors are more likely to form a relationship if they have similar policy preferences. The second explanation, from network theory, predicts that the likelihood of a tie between two actors depends on the presence of certain relationships with other actors. Our data consist of a unique combination of actors' policy positions and their network relations over time in the Council of the European Union. We find evidence that both types of explanations matter, although there seems to be variation in the extent to which preference similarity affects network evolution. We consider the implications of these findings for understanding the decision-making in the Council.

scholarly journals A Novel Wireless Sensor Network Evolution Model Based on Energy-Efficiency

2017 ◽  
Vol 13 (03) ◽  
pp. 4 ◽  
Author(s):  
Hui Gao ◽  
Zhixian Yang
Keyword(s):  
Preferential Attachment ◽  
Influence Factors ◽  
Network Evolution ◽  
Evolution Model ◽  
Wireless Sensor ◽  
Font Size ◽  
Total Energy Consumption ◽  
Scale Free ◽  
Random Node ◽  
Attachment Mechanism

<span style="font-family: 'Times New Roman',serif; font-size: 12pt; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">The Barabási–Albert (BA) model is a famous complex network model that generates scale-free networks. Wireless sensor networks (WSNs) had been thought to be approximately scale-free through lots of empirical research. Based on the BA model, we propose an evolution model for WSNs. According to actual influence factors such as the remainder energy of each sensor and physical link capability of each sensor, our evolution model constructs WSNs by using a preferential attachment mechanism. Through simulation and analysis, we can prove that our evolution model would make the total energy consumption of the WSNs more efficient and have a superior random node error tolerance.</span>

The N-star network evolution model

2019 ◽  
Vol 56 (2) ◽  
pp. 416-440 ◽  
Author(s):  
István Fazekas ◽  
Csaba Noszály ◽  
Attila Perecsényi
Keyword(s):  
Power Law ◽  
Preferential Attachment ◽  
Network Evolution ◽  
Evolution Model ◽  
Asymptotic Power ◽  
Star Network ◽  
Power Law Distributions

AbstractA new network evolution model is introduced in this paper. The model is based on cooperations of N units. The units are the nodes of the network and the cooperations are indicated by directed links. At each evolution step N units cooperate, which formally means that they form a directed N-star subgraph. At each step either a new unit joins the network and it cooperates with N − 1 old units, or N old units cooperate. During the evolution both preferential attachment and uniform choice are applied. Asymptotic power law distributions are obtained both for in-degrees and for out-degrees.

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