Multi-scenario simulation on the impact of China's electricity bidding policy based on complex networks model

Energy Policy ◽  
2021 ◽  
Vol 158 ◽  
pp. 112573
Author(s):  
Di Wang ◽  
Zhiyuan Zhang ◽  
Xiaodi Yang ◽  
Yanfang Zhang ◽  
Yuman Li ◽  
...  
Keyword(s):  
Complex Networks ◽  
Scenario Simulation ◽  
The Impact

scholarly journals Visualizing real-world networks

2021 ◽  
Author(s):  
Lyndsay Roach
Keyword(s):  
Complex Networks ◽  
Real World ◽  
The Internet ◽  
Network Data ◽  
Community Structures ◽  
Large Networks ◽  
Computing Power ◽  
On Line ◽  
Using Data ◽  
The Impact

The study of networks has been propelled by improvements in computing power, enabling our ability to mine and store large amounts of network data. Moreover, the ubiquity of the internet has afforded us access to records of interactions that have previously been invisible. We are now able to study complex networks with anywhere from hundreds to billions of nodes; however, it is difficult to visualize large networks in a meaningful way. We explore the process of visualizing real-world networks. We first discuss the properties of complex networks and the mechanisms used in the network visualizing software Gephi. Then we provide examples of voting, trade, and linguistic networks using data extracted from on-line sources. We investigate the impact of hidden community structures on the analysis of these real-world networks.

scholarly journals The Impact of Countries’ Roles on the International Photovoltaic Trade Pattern: The Complex Networks Analysis

2016 ◽  
Vol 8 (4) ◽  
pp. 313 ◽  
Author(s):  
Qing Guan ◽  
Haizhong An ◽  
Xiaoqing Hao ◽  
Xiaoliang Jia
Keyword(s):  
Complex Networks ◽  
Trade Pattern ◽  
Networks Analysis ◽  
The Impact

Analysis of the impact of Sino-US trade friction on China’s stock market based on complex networks

2020 ◽  
Vol 52 ◽  
pp. 101185 ◽  
Author(s):  
Yanshuang Li ◽  
Xintian Zhuang ◽  
Jian Wang ◽  
Weiping Zhang
Keyword(s):  
Stock Market ◽  
Complex Networks ◽  
Trade Friction ◽  
The Impact

scholarly journals Finite-Time Synchronization for a Class of Multiweighted Complex Networks with Markovian Switching and Time-Varying Delay

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-25
Author(s):  
Ying Liu ◽  
Fei Chen ◽  
Bin Yang ◽  
Xin Wang ◽  
Weiming Wang
Keyword(s):  
Complex Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Time Estimation ◽  
Markovian Switching ◽  
Convergence Time ◽  
Time Varying ◽  
Time Varying Delay ◽  
The Impact ◽  
Varying Delay

In this paper, we investigate the finite-time synchronization control for a class of nonlinear coupled multiweighted complex networks (NCMWCNs) with Markovian switching and time-varying delay analytically and quantitatively. The value of this study lies in four aspects: First, it designs the finite-time synchronization controller to make the NCMWCNs with Markovian switching and time-varying delay achieve global synchronization in finite time. Second, it derives two kinds of finite-time estimation approaches by analyzing the impact of the nonlinearity of nonlinear coupled function on synchronization dynamics and synchronization convergence time. Third, it presents the relationship between Markovian switching parameters and synchronization problems of subsystems and the overall system. Fourth, it provides some numerical examples to demonstrate the effectiveness of the theoretical results.

The Impact of Complex Network Models to EDAs

2014 ◽  
Vol 926-930 ◽  
pp. 3290-3293
Author(s):  
Cai Chang Ding ◽  
Wen Xiu Peng ◽  
Wei Ming Wang
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Optimization Problem ◽  
Wide Spectrum ◽  
Network Models ◽  
Problem Structure ◽  
Topological Characteristics ◽  
Complex Network Models ◽  
The Impact

The study conducted in this paper is mainly driven by the topological characteristics of the structures that the interactions among the variables of the problems provide. Taking as reference the emergent field of complex networks, we generate a wide spectrum of networks that will serve as problem structures. Then, the impact that the topological characteristics of those networks have, both in the hardness of the optimization problem and in the behavior of the EDA, is analyzed. This reveals a relationship among the topology of the problem structure, the difficulty of the problems and the dependences that the algorithm needs to learn in order to solve the problems.

scholarly journals The impact of chaotic saddles on the synchronization of complex networks of discrete-time units

2021 ◽  
Vol 2 (3) ◽  
pp. 035002
Author(s):  
Everton S Medeiros ◽  
Rene O Medrano-T ◽  
Iberê L Caldas ◽  
Ulrike Feudel
Keyword(s):  
Complex Networks ◽  
Discrete Time ◽  
The Impact

scholarly journals A tensor-based framework for studying eigenvector multicentrality in multilayer networks

2019 ◽  
Vol 116 (31) ◽  
pp. 15407-15413 ◽  
Author(s):  
Mincheng Wu ◽  
Shibo He ◽  
Yongtao Zhang ◽  
Jiming Chen ◽  
Youxian Sun ◽  
...  
Keyword(s):  
Complex Networks ◽  
Prior Knowledge ◽  
General Framework ◽  
Single Layer ◽  
Structure And Function ◽  
Centrality Measures ◽  
Multilayer Networks ◽  
And Function ◽  
The Impact ◽  
Insight Into

Centrality is widely recognized as one of the most critical measures to provide insight into the structure and function of complex networks. While various centrality measures have been proposed for single-layer networks, a general framework for studying centrality in multilayer networks (i.e., multicentrality) is still lacking. In this study, a tensor-based framework is introduced to study eigenvector multicentrality, which enables the quantification of the impact of interlayer influence on multicentrality, providing a systematic way to describe how multicentrality propagates across different layers. This framework can leverage prior knowledge about the interplay among layers to better characterize multicentrality for varying scenarios. Two interesting cases are presented to illustrate how to model multilayer influence by choosing appropriate functions of interlayer influence and design algorithms to calculate eigenvector multicentrality. This framework is applied to analyze several empirical multilayer networks, and the results corroborate that it can quantify the influence among layers and multicentrality of nodes effectively.

scholarly journals Impact of Immunization Strategies on the Dynamics of Social Contagions

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hao Peng ◽  
Wangxin Peng ◽  
Dandan Zhao ◽  
Zhaolong Hu ◽  
Jianmin Han ◽  
...  
Keyword(s):  
Complex Networks ◽  
Threshold Model ◽  
Network Heterogeneity ◽  
Immunization Strategies ◽  
Spreading Dynamics ◽  
Theoretical Predictions ◽  
Underlying Network ◽  
Edge Based ◽  
The Individual ◽  
The Impact

Immunization strategies on complex networks are effective methods to control the spreading dynamics on complex networks, which change the topology and connectivity of the underlying network, thereby affecting the dynamics process of propagation. Here, we use a non-Markovian threshold model to study the impact of immunization strategies on social contagions, in which the immune index greater than (or equal to) 0 corresponds to targeted (random) immunization, and when the immune index is less than 0, the probability of an individual being immunized is inversely related to the degree of the individual. A generalized edge-based compartmental theory is developed to analyze the dynamics of social contagions under immunization, and theoretical predictions are very consistent with simulation results. We find that increasing the immune index or increasing the immune ratio will reduce the final adoption size and increase the outbreak threshold, in other words, make the residual network after immunization not conducive to social contagions. Interestingly, enhancing the network heterogeneity is proved to help improve the immune efficiency of targeted immunization. Besides, the dependence of the outbreak threshold on the network heterogeneity is correlated with the immune ratio and immune index.

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