A Dynamic Evolution Model of Airline Networks

2017 ◽  
Vol 34 (5) ◽  
pp. 058902
Author(s):  
Ze-Jun Xie ◽  
Lu-Man Zhang ◽  
Sheng-Feng Deng ◽  
Wei Li
Keyword(s):  
Evolution Model ◽  
Dynamic Evolution ◽  
Airline Networks

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.

scholarly journals The Porosity Dynamic Model of the Compacted Broken Coal

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xuefeng Han ◽  
Tingxiang Chu ◽  
Minggao Yu ◽  
Jiangkun Chao ◽  
Zhihui Ma ◽  
...  
Keyword(s):  
Spontaneous Combustion ◽  
Axial Stress ◽  
Fractal Theory ◽  
Dynamic Change ◽  
Strain Curve ◽  
Fractal Model ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Permeability Evolution ◽  
Loading Test

In order to study the dynamic change law of the porosity of the compacted broken coal under different axial stress loading, based on the environment of the broken and compacted coal in the gob, aiming at the influence of the porosity on the spontaneous combustion of the coal, combined with the fractal theory, the fractal model of the porosity of the broken coal is established. A self-designed “testing device for permeability evolution and spontaneous combustion characteristics of crushed coal under pressure” is used to carry out axial loading test on selected coal samples in the gob. By comparing and analyzing the calculated results of void dynamic evolution model and experimental data, it is found that the relative error of void dynamic evolution model is between 2.8% and 6.2%, which meets the engineering needs. According to the stress-strain curve, initial accumulation state parameters, fractal dimension of initial crushing, and particle size distribution, the change of porosity under different compacted conditions can be predicted by the model, which has certain significance for identifying the change of compacted broken coal porosity and analyzing the process of coal spontaneous combustion and oxidation.

scholarly journals A quality-of-service-aware dynamic evolution model for space–ground integrated network

2017 ◽  
Vol 13 (8) ◽  
pp. 155014771772864 ◽  
Author(s):  
Zhuo Yi ◽  
Xuehui Du ◽  
Ying Liao ◽  
Lifeng Cao
Keyword(s):  
Quality Of Service ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Power Law Distribution ◽  
Integrated Network ◽  
Complex Network Theory

Space–ground integrated network, a strategic, driving, and irreplaceable infrastructure, guarantees the development of economic and national security. However, its natures of limited resources, frequent handovers, and intermittently connected links significantly reduce the quality of service. To address this issue, a quality-of-service-aware dynamic evolution model is proposed based on complex network theory. On one hand, a quality-of-service-aware strategy is adopted in the model. During evolution phases of growth and handovers, links are established or deleted according to the quality-of-service-aware preferential attachment following the rule of better quality of service getting richer and worse quality of service getting poor or to die. On the other hand, dynamic handover of nodes and intermittent connection of links are taken into account and introduced into the model. Meanwhile, node heterogeneity is analyzed and heterogeneous nodes are endowed with discriminate interactions. Theoretical analysis and simulations are utilized to explore the degree distribution and its characteristics. Results reveal that this model is a scale-free model with drift power-law distribution, fat-tail and small-world effect, and drift character of degree distribution results from dynamic handover. Furthermore, this model exerts well fault tolerance and attack resistance compared to signal-strength-based strategy. In addition, node heterogeneity and quality-of-service-aware strategy improve the attack resistance and overall quality of service of space–ground integrated network.

Dynamic evolution model of isothermal voids and shocks

2009 ◽  
Vol 323 (1) ◽  
pp. 17-40 ◽  
Author(s):  
Yu-Qing Lou ◽  
Xiang Zhai
Keyword(s):  
Evolution Model ◽  
Dynamic Evolution

scholarly journals Characterization and Evolution of a Digital Economy Ecosystem Based on an Interspecies Competition Model

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Han Zhou ◽  
Xiaorui Han ◽  
Le Wang
Keyword(s):  
Decision Making ◽  
Equilibrium Point ◽  
Digital Economy ◽  
Operating Conditions ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Model Parameters ◽  
Entrepreneurial Ecosystem ◽  
Interspecies Competition ◽  
The Relationship

This paper provides an in-depth study and analysis of the characterization of the digital economy ecosystem and the mechanism of eye-flowering through the method of interspecies competition. The evolutionary game model of symbiotic decision-making in the entrepreneurial ecosystem is constructed, the evolutionary process of symbiotic decision-making of subjects is analyzed through mathematical derivation, and the symbiotic decision-making process of subjects is simulated through computer simulation to answer how the subjects of the entrepreneurial ecosystem make symbiotic decisions and explore the mechanism of symbiotic formation of the entrepreneurial ecosystem. Then, based on the ecological perspective, the symbiotic evolution model of entrepreneurial ecosystem subjects is constructed from the subject level, the equilibrium point of the evolution of entrepreneurial ecosystem subjects, the stability conditions, and the relationship between the equilibrium point and the symbiosis model are analyzed, and the symbiotic evolution paths of entrepreneurial ecosystem subjects under different symbiosis modes, initial population size, maximum size, and natural growth rate are presented with simulation experiments, respectively. The main characteristics and manifestations of the dynamic evolution of the platform ecosystem are analyzed, and the key competitive factors that determine the dynamic evolution of the platform ecosystem are depicted. Then, according to the inherent characteristic laws of the platform ecosystem, the complex network approach is applied to construct a dynamic evolution model with originality and wide applicability for the change of bilateral user scale. Based on the dynamic evolution process, the relationship between model parameters and business performance is explored, and the trajectory of bilateral user size change over time and the range of parameters are derived by numerical calculation. Finally, using Monte Carlo simulation methods, the dynamic evolution model is used to predict the future operating conditions of platform enterprises, providing a valuation basis for investors to make investment decisions and helping platform managers to formulate business strategies.

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