scholarly journals Optimization of Crude Oil Trade Structure: A Complex Network Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Gaogao Dong ◽  
Ting Qing ◽  
Lixin Tian ◽  
Ruijin Du ◽  
Jingjing Li
Keyword(s):  
Crude Oil ◽  
Complex Network ◽  
Minimum Spanning Tree ◽  
Supply And Demand ◽  
Topological Analysis ◽  
Energy System ◽  
Power Law Distribution ◽  
Trade Network ◽  
Complex Network Theory ◽  
Trade Structure

With the contradiction between supply and demand being intensified, the unreasonable crude oil trade structure has become increasingly prominent. Therefore, optimizing the supply and demand structure of the global crude oil trade is an urgent problem, which has become one of the crucial factors affecting the energy strategy and economic development of each country. This paper builds an optimization model that aims at minimizing crude oil trade costs based on the complex network theory. Meanwhile, an optimal solution generation approach is proposed and developed in this paper. Compared with the preoptimized trade network, the proposed model can effectively reduce the trade cost. By topological analysis of the trade network and its optimal configuration, we obtain that both the preoptimized and optimized crude oil trade networks follow power-law distribution. By using the minimum spanning tree, we find that the major crude oil net exporting countries have the most significant influence and are at the core in the optimized trade structure. This work focuses on the sustainable development of the global crude oil trade and provides a fresh perspective for the optimal crude oil trade system. Moreover, the methodology and model may be applied in the investigation of optimization for other energy system structures.

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.

Complexity Analysis of Public Transportation Network in Zhangjiagang City Using Complex Network Theory

2012 ◽  
Vol 546-547 ◽  
pp. 1211-1216
Author(s):  
Yong Wang ◽  
Ta Zhou
Keyword(s):  
Complex Network ◽  
Public Transportation ◽  
Path Length ◽  
Complexity Analysis ◽  
Transportation Network ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
Public Transportation Network

Public transportation network has been proven that it can be simulated as a complex network. In this paper, a bus transport system of Zhangjiagang city is considered. Network degree distribution, average path length, and clustering coefficient are utilized as criteria to analyze as the complexity of the network. Experimental results show that the network which is in line with power-law distribution has a smaller average path length and a large clustering coefficient. It also indicates that, the networks of Zhangjiagang public bus system are not a small-world network with scale-free property.

A study on the evolution of port logistics network based on complex theory: A case study of key coastal ports in China

2021 ◽  
pp. 1-11
Author(s):  
Xu Xu ◽  
Yanbing Yang ◽  
Yi Liu
Keyword(s):  
Complex Network ◽  
Network Evolution ◽  
Clustering Coefficient ◽  
Belt And Road Initiative ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
Network Characteristics ◽  
Real Network ◽  
Belt And Road ◽  
The Belt And Road

In order to promote the construction of “The Belt and Road” Initiative, we construct the complex network evolution model based on the complex network theory and node attractiveness. We select the relevant 2017 data of 18 coastal ports mentioned in the Belt and Road Initiative, and verify the validity of the model by comparing the network eigenvalues between evolving network and real network. The results show that the average distances between ports are short, clustering coefficient and dependence of hub ports are high, its topological structure has scale-free network characteristics and fits the power law distribution. Meanwhile, we study the change of network characteristics of the evolutionary network and real network under deliberate attack and random attack. The statistics show that the robustness is weak under deliberate attack but strong under random attack. These are great reference to the construction and development of China’s Belt and Road Initiative.

scholarly journals Structure Characteristics and Influencing Factors of Cross-Border Electricity Trade: A Complex Network Perspective

2021 ◽  
Vol 13 (11) ◽  
pp. 5797
Author(s):  
Yue Pu ◽  
Yunting Li ◽  
Yingzi Wang
Keyword(s):  
Complex Network ◽  
Industrial Structure ◽  
Structural Characteristics ◽  
Supply And Demand ◽  
Trade Network ◽  
Trade Networks ◽  
Cross Border ◽  
Electricity Trade ◽  
Border Trade ◽  
The Common

Electricity is one of the most widely used forms of energy. However, environmental pollution from electricity generation and the mismatch between electricity supply and demand have long been bothering economies across the world. Under this background, cross-border electricity trade provides a new direction for sustainable development. Based on the complex network approach, this paper aims to explore the structural characteristics and evolution of cross-border electricity trade networks and to figure out the factors influencing the formation of the network by using the more advanced network analysis method—ERGM. The results show that: (1) The scale of the electricity trade network is expanding, but there are still many economies not involved. (2) The centrality of the network shifts from west to east. The level of internal electricity interconnection is high in Europe, and Asian countries’ coordination role in cross-border electricity trade networks is enhanced. (3) Cross-border electricity trade helps to reduce CO2 emissions, achieve renewable energy transformation, and reduce power supply and demand mismatch. Large gaps in GDP, electricity prices, industrial structure, geographical distance and institutional distance between economies are not conducive to form the cross-border trade network, while the common language is on the contrary.

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 Evolution of the Global Agricultural Trade Network and Policy Implications for China

2019 ◽  
Vol 12 (1) ◽  
pp. 192 ◽  
Author(s):  
Wenli Qiang ◽  
Shuwen Niu ◽  
Xiang Wang ◽  
Cuiling Zhang ◽  
Aimin Liu ◽  
...  
Keyword(s):  
Supply And Demand ◽  
Developed Countries ◽  
Agricultural Trade ◽  
Agricultural Products ◽  
Policy Implications ◽  
Cumulative Distribution ◽  
Node Degree ◽  
Power Law Distribution ◽  
Trade Network ◽  
Monetary Value

Global agricultural trade plays an essential role in balancing supply and demand regarding agricultural products worldwide. Based on complex network theory, two types of agricultural trade networks weighted by the physical quantity and monetary value were built. In both networks, eight groups of agricultural products showed diverse variation in time and space. During 1986 to 2016, the total physical trade increased by 2.55 times with a gradual growth process, and total monetary value increased 1.98 times with fluctuation. The cumulative distribution of node degree and strength followed power-law distribution. Scale expansion and structure complexity of both networks reflected heterogeneity between nodes and the trend of agricultural economic globalization. Meeting demand and seeking greater returns are the main drivers of global agricultural trade development. Mainly developed countries occupied the important positions in the global agricultural trade network, but some emerging economies such as China, Brazil, and India became important sources of demand and supply. China not only needs to fully use international resources to meet demand for agricultural products, but also needs to ensure its own food security through multiple countermeasures.

Deep learning and complex network theory based analysis on socialized manufacturing resources utilisations and an application case study

2021 ◽  
pp. 1063293X2110031
Author(s):  
Maolin Yang ◽  
Auwal H Abubakar ◽  
Pingyu Jiang
Keyword(s):  
Deep Learning ◽  
Complex Network ◽  
Network Models ◽  
Neural Network Models ◽  
Complex Network Theory ◽  
New Type ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Resource Characteristics

Social manufacturing is characterized by its capability of utilizing socialized manufacturing resources to achieve value adding. Recently, a new type of social manufacturing pattern emerges and shows potential for core factories to improve their limited manufacturing capabilities by utilizing the resources from outside socialized manufacturing resource communities. However, the core factories need to analyze the resource characteristics of the socialized resource communities before making operation plans, and this is challenging due to the unaffiliated and self-driven characteristics of the resource providers in socialized resource communities. In this paper, a deep learning and complex network based approach is established to address this challenge by using socialized designer community for demonstration. Firstly, convolutional neural network models are trained to identify the design resource characteristics of each socialized designer in designer community according to the interaction texts posted by the socialized designer on internet platforms. During the process, an iterative dataset labelling method is established to reduce the time cost for training set labelling. Secondly, complex networks are used to model the design resource characteristics of the community according to the resource characteristics of all the socialized designers in the community. Two real communities from RepRap 3D printer project are used as case study.

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