scholarly journals Study on the Evolution Characteristics of International Nickel Ores Trade from Perspective of Complex Networks

2020 ◽  
Vol 143 ◽  
pp. 02050
Author(s):  
Yun Ding
Keyword(s):  
International Trade ◽  
Network Theory ◽  
The United States ◽  
Distribution Analysis ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
Core Country ◽  
Evolution Characteristics ◽  
Nickel Ores ◽  
Trading Network

In order to analyze the evolution characteristics of nickel ores international trade structure, this paper builds up the network model by adopting the complex network theory. Based on the International trade data of nickel ores from 2007 to 2018, we analyze the overall pattern of trade network, core country identification and the power-law distribution analysis. According to the research, it is found that China and the United States have a strong influence in the international nickel ores trading network. The more nickel producing counties participated in this trade and the international nickel ore market commenced to globalization.

Research on the Structure of Peer-to-Peer Overlay Based on the Complex Network Theory

2012 ◽  
Vol 263-266 ◽  
pp. 1096-1099
Author(s):  
Zhi Yong Jiang
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Degree Distribution ◽  
Path Length ◽  
Small World ◽  
Peer To Peer ◽  
Clustering Coefficient ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
The Mean

Relationship between nodes in peer-to-peer overlay, currently becomes a hot topic in the field of complex network. In this paper a model of peer-to-peer overlay was purposed. And then the paper focused on figuring out the mean-shortest path length (MSPL), clustering coefficient (CC) and the degree of every node which allowed us to discover the degree distribution. The results show that the degree distribution function follows approximately power law distribution and the network possesses notable clustering and small-world properties.

scholarly journals A Model for Evolution of Investors Behavior in Stock Market Based on Reinforcement Learning in Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiaqun Liu ◽  
Yaming Zhuang ◽  
Jinsheng Li ◽  
Wei Zhou
Keyword(s):  
Reinforcement Learning ◽  
Learning Theory ◽  
Network Topology ◽  
Mathematical Analysis ◽  
Network Theory ◽  
Institutional Investors ◽  
Investment Decisions ◽  
Individual Investors ◽  
Complex Network Theory ◽  
Evolution Characteristics

This paper builds an evolution model of investors behavior based on the reinforcement learning in multiplex networks. Due to the heterogeneity of learning characteristics of bounded rational investors in investment decisions, we consider, respectively, the evolution mechanism of individual investors and institutional investors on the complex network theory and reinforcement learning theory. We perform mathematical analysis and simulation to further explain the evolution characteristics of investors behavior. The conclusions are drawn as follows: First, the intensity of returns competition among institutional investors and the forgetting effect both have an impact on the equilibrium of their evolution as to all institutional investors and individual investors. Second, the network topology significantly affects the behavioral evolution of individual investors compared with institutional investors.

scholarly journals Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-31 ◽  
Author(s):  
Yong Tang ◽  
Jason Jie Xiong ◽  
Zi-Yang Jia ◽  
Yi-Cheng Zhang
Keyword(s):  
Network Analysis ◽  
Financial Markets ◽  
Portfolio Management ◽  
Network Theory ◽  
Stock Markets ◽  
Hierarchical Structures ◽  
The United States ◽  
Dynamics Modeling ◽  
Financial Network ◽  
Complex Network Theory

Policy makings and regulations of financial markets rely on a good understanding of the complexity of financial markets. There have been recent advances in applying data-driven science and network theory into the studies of social and financial systems. Financial assets and institutions are strongly connected and influence each other. It is essential to study how the topological structures of financial networks could potentially influence market behaviors. Network analysis is an innovative method to enhance data mining and knowledge discovery in financial data. With the help of complex network theory, the topological network structures of a market can be extracted to reveal hidden information and relationships among stocks. In this study, two major markets of the most influential economies, China and the United States, are systematically studied from the perspective of financial network analysis. Results suggest that the network properties and hierarchical structures are fundamentally different for the two stock markets. The patterns embedded in the price movements are revealed and shed light on the market dynamics. Financial policymakers and regulators can gain inspiration from these findings for applications in policy making, regulations design, portfolio management, risk management, and trading.

scholarly journals Structural Analysis of Bus Networks Using Indicators of Graph Theory and Complex Network Theory

2017 ◽  
Vol 11 (1) ◽  
pp. 92-100 ◽  
Author(s):  
Hui Zhang
Keyword(s):  
Graph Theory ◽  
Complex Network ◽  
Adjacency Matrix ◽  
Network Theory ◽  
Weighted Average ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
Path Distance ◽  
Bus Network ◽  
Bus Networks

The structure of bus network is very significant for bus system. To evaluate the performance of the structure of bus network, indicators basing on graph theory and complex network theory are proposed. Three forms of matrices comprising line-station matrix, weighted adjacency matrix and adjacency matrix under space P are used to represent the bus network. The paper proposes a shift power law distribution which is related average degree of network to fit the degree distribution and a method to calculate the average transfer time between any two stations using adjacency matrix under P space. Moreover, this paper proposes weighted average shortest path distance and transfer efficiency to evaluate the bus network. The results show that the indicators that we introduce, effectively reflect properties of bus network.

scholarly journals Using Network Theory to Explore BIM Application Barriers for BIM Sustainable Development in China

2020 ◽  
Vol 12 (8) ◽  
pp. 3190
Author(s):  
Yongliang Deng ◽  
Jinyun Li ◽  
Qiuting Wu ◽  
Shuangshuang Pei ◽  
Na Xu ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Network Theory ◽  
Path Length ◽  
Small World ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Information Modeling ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
Scale Free

Building Information Modeling (BIM) technology has promoted the development of the architecture, engineering, and construction (AEC) industry, but has encountered many barriers to its application in China. Therefore, identifying the barriers to BIM application and capturing their interactions are essential in order to control and eliminate the determined barriers. From this standpoint, 23 BIM application barriers were identified through a literature review and expert interviews. Furthermore, the interactions among them were determined based on the Delphi method, which was the foundation for establishing the BIM application barrier network (BABN). Then, the software Pajek was employed to construct the network model and reveal its topological characteristics based on complex network theory, including degree, betweenness, eigenvector, clustering coefficient, network diameter, and average path length. As indicated by the results, BABN possesses scale-free network property because its cumulative degree distribution obeys power–law distribution. BABN is also a small-world network, due to its relatively high clustering coefficient as well as small average path length, implying that barrier propagation in BABN is fast. In addition, the results are discussed and recommendations are proposed. This research will help BIM stakeholders to develop coping strategies to control and eliminate BIM application barriers for the sake of driving BIM sustainable development.

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