scholarly journals Classification of Literary Works: Fractality and Complexity of the Narrative, Essay, and Research Article

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 904
Author(s):  
Aldo Ramirez-Arellano
Keyword(s):  
Complex Network ◽  
Path Length ◽  
Research Topic ◽  
Clustering Coefficient ◽  
Node Degree ◽  
Original Text ◽  
Literary Works ◽  
Research Article ◽  
A Current

A complex network as an abstraction of a language system has attracted much attention during the last decade. Linguistic typological research using quantitative measures is a current research topic based on the complex network approach. This research aims at showing the node degree, betweenness, shortest path length, clustering coefficient, and nearest neighbourhoods’ degree, as well as more complex measures such as: the fractal dimension, the complexity of a given network, the Area Under Box-covering, and the Area Under the Robustness Curve. The literary works of Mexican writers were classify according to their genre. Precisely 87% of the full word co-occurrence networks were classified as a fractal. Also, empirical evidence is presented that supports the conjecture that lemmatisation of the original text is a renormalisation process of the networks that preserve their fractal property and reveal stylistic attributes by genre.

scholarly journals Complex Network Theory for Water Distribution Networks Analysis

10.29007/w1bk ◽  
2018 ◽  
Author(s):  
Antonietta Simone ◽  
Luca Ridolfi ◽  
Luigi Berardi ◽  
Daniele Laucelli ◽  
Orazio Giustolisi
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Path Length ◽  
Water Distribution ◽  
Distribution Networks ◽  
Networked Systems ◽  
Clustering Coefficient ◽  
Complex Network Theory ◽  
Connectivity Structure

Performance of networked systems greatly depends on their topologic or connectivity structure. Nowadays, the analysis of the relevant features influencing the emerging behavior of networked systems is possible because of the increasing computational power and availability of information. Complex Network Theory classifies the connectivity structures of real systems using the nodal degree, the average path length, the clustering coefficient and the probability of connection. However, networked city infrastructures, e.g. water distribution networks (WDNs), are constrained by the spatial characteristics of the environment where they are laid. Therefore, networked infrastructures are classified as spatial networks and the classification of their connectivity structure requires a modification of the classic framework. To this purpose, the paper proposes a classification of WDNs using the neighbourhood nodal degree instead of the classic degree, the network size instead of the probability of connection and the classic average path length. The research will show that the clustering coefficient is not useful to describe the behavior of these constrained systems.

scholarly journals A Complex Network Approach for Quantitative Characterization and Robustness Analysis of Sandstone Pore Network Structure

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yuhao Hu ◽  
Guannan Liu ◽  
Feng Gao ◽  
Fengtian Yue ◽  
Tao Gao
Keyword(s):  
Pore Structure ◽  
Complex Network ◽  
Degree Distribution ◽  
Path Length ◽  
Robustness Analysis ◽  
Pore Network ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Random Disturbance ◽  
Pagerank Algorithm

The rational characterization and quantitative analysis of the complex internal pore structure of rock is the foundation to solve many underground engineering problems. In this paper, CT imaging technology is used to directly characterize the three-dimensional pore network topology of sandstone with different porosity. Then, in view of the problem, which is difficult to quantify the detailed topological structure of the sandstone pore networks in the previous study, the new complex network theory is used to characterize the pore structure. PageRank algorithm is based on the number of connections between targets as a measure index to rank the targets, so the network degree distribution, average path length, clustering coefficient, and robustness based on PageRank algorithm and permeability-related topological parameters are studied. The research shows that the degree distribution of sandstone pore network satisfies power law distribution, and it can be characterized by scale-free network model. The permeability of rock is inversely proportional to the average path length of sandstone network. The sandstone pore network has strong robustness to random disturbance, while a small number of pores with special topological properties play a key role in the macroscopic permeability of sandstone. This study attempts to provide a new perspective of quantifying the microstructure of the pore network of sandstone and revealing the microscopic structure mechanism of macroscopic permeability of pore rocks.

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.

AN IDEAL DISASSORTATIVE NETWORK AND SYNCHRONIZATION

2006 ◽  
Vol 16 (10) ◽  
pp. 3093-3102 ◽  
Author(s):  
DONG CHENGDONG ◽  
LIU ZENGRONG
Keyword(s):  
Dynamic System ◽  
Complex Network ◽  
Network Topology ◽  
Path Length ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Novel Complex ◽  
The Impact

This paper proposes a novel complex network with disassortative property based on multicenter networks. The average path length and clustering coefficient of the network are calculated, and the impact on the network topology is investigated. A simple dynamic system established on the proposed network is used to analyze how the disassortative property of the network affects synchronization.

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.

scholarly journals Classification of cardiovascular time series based on different coupling structures using recurrence networks analysis

2013 ◽  
Vol 371 (1997) ◽  
pp. 20110623 ◽  
Author(s):  
Gonzalo Marcelo Ramírez Ávila ◽  
Andrej Gapelyuk ◽  
Norbert Marwan ◽  
Thomas Walther ◽  
Holger Stepan ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Time Series ◽  
Path Length ◽  
Clustering Coefficient ◽  
Early Prediction ◽  
Quadratic Discriminant Analysis ◽  
Novel Approach ◽  
Networks Analysis

We analyse cardiovascular time series with the aim of performing early prediction of preeclampsia (PE), a pregnancy-specific disorder causing maternal and foetal morbidity and mortality. The analysis is made using a novel approach, namely the ε -recurrence networks applied to a phase space constructed by means of the time series of the variabilities of the heart rate and the blood pressure (systolic and diastolic). All the possible coupling structures among these variables are considered for the analysis. Network measures such as average path length, mean coreness, global clustering coefficient and scale-local transitivity dimension are computed and constitute the parameters for the subsequent quadratic discriminant analysis. This allows us to predict PE with a sensitivity of 91.7 per cent and a specificity of 68.1 per cent, thus validating the use of this method for classifying healthy and preeclamptic patients.

The Study on Wireless Sensor Network Topological Structure for Improving Network Energy Utilization

2013 ◽  
Vol 443 ◽  
pp. 509-512
Author(s):  
Yan Zhu ◽  
Yun Yu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Complex Network ◽  
Path Length ◽  
Small World ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Wireless Sensor ◽  
Small World Network

Based on the complex network property of wireless sensor networks, this study focus on the topology of wireless sensor network and carry out series simulation according to complex network research methods. The characteristic of topology for the wireless sensor network is probed in the experiment. The degree distribution, clustering coefficient and average path length are analyzed during the experimental process. Our results verify that the topology of wireless sensor network is neither regular nor random. It is between random network and small-world network which has comparatively smaller average path length and bigger cluster coefficient. In order to form a network that is similar to the property of small-world network, which can reduce network energy consumption by decrease the average hops, our experiment constructs a network model which has significant small-world network characteristic. The results indicate that the added small sum of long range edges in the network will not increase the network load while it can reduce the energy consumption of the network effectively.

Technological Alliance Networks Analysis under Complex Network Perspective - Case of China's TD-SCDMA Industry

2013 ◽  
Vol 756-759 ◽  
pp. 2774-2778
Author(s):  
Liang Mei
Keyword(s):  
Complex Network ◽  
Path Length ◽  
Small World ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Structure Characteristics ◽  
Alliance Networks ◽  
Different Types ◽  
Networks Analysis

This paper discusses the structure characteristics of Chinas TD-SCDMA industry alliance from complex network perspective. We use the basic two parametersaverage path length and clustering coefficient to do the analysis. Results show that comparing to the different types of complex network, Chinas TD-SCDMA industry alliance has relatively high clustering coefficient and low average path length, implicating the obvious small-world characteristic.

scholarly journals Complex-network description of seismicity

2006 ◽  
Vol 13 (2) ◽  
pp. 145-150 ◽  
Author(s):  
S. Abe ◽  
N. Suzuki
Keyword(s):  
Complex Network ◽  
Power Law ◽  
Seismic Data ◽  
Path Length ◽  
Clustering Coefficient ◽  
Random Networks ◽  
Network Approach ◽  
Scale Free ◽  
Undirected Network ◽  
Small Work

Abstract. The seismic data taken in California and Japan are mapped to growing random networks. It is shown in the undirected network picture that these earthquake networks are scale-free and small-work networks with the power-law connectivity distributions, the large values of the clustering coefficient, and the small values of the average path length. It is demonstrated how the present network approach reveals complexity of seismicity in a novel manner.

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