Brain Knowledge Graph Analysis Based on Complex Network Theory

2016 ◽  
pp. 211-220 ◽  
Author(s):  
Hongyin Zhu ◽  
Yi Zeng ◽  
Dongsheng Wang ◽  
Bo Xu
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Knowledge Graph ◽  
Graph Analysis ◽  
Complex Network Theory

scholarly journals Ecological Network Optimization in Urban Central District Based on Complex Network Theory: A Case Study with the Urban Central District of Harbin

2021 ◽  
Vol 18 (4) ◽  
pp. 1427
Author(s):  
Shuang Song ◽  
Dawei Xu ◽  
Shanshan Hu ◽  
Mengxi Shi
Keyword(s):  
Complex Network ◽  
Network Optimization ◽  
Network Theory ◽  
Habitat Destruction ◽  
Landscape Patterns ◽  
Ecological Network ◽  
Complex Network Theory ◽  
Ecological Corridors ◽  
Low Degree ◽  
Central District

Habitat destruction and declining ecosystem service levels caused by urban expansion have led to increased ecological risks in cities, and ecological network optimization has become the main way to resolve this contradiction. Here, we used landscape patterns, meteorological and hydrological data as data sources, applied the complex network theory, landscape ecology, and spatial analysis technology, a quantitative analysis of the current state of landscape pattern characteristics in the central district of Harbin was conducted. The minimum cumulative resistance was used to extract the ecological network of the study area. Optimized the ecological network by edge-adding of the complex network theory, compared the optimizing effects of different edge-adding strategies by using robustness analysis, and put forward an effective way to optimize the ecological network of the study area. The results demonstrate that: The ecological patches of Daowai, Xiangfang, Nangang, and other old districts in the study area are small in size, fewer in number, strongly fragmented, with a single external morphology, and high internal porosity. While the ecological patches in the new districts of Songbei, Hulan, and Acheng have a relatively good foundation. And ecological network connectivity in the study area is generally poor, the ecological corridors are relatively sparse and scattered, the connections between various ecological sources of the corridors are not close. Comparing different edge-adding strategies of complex network theory, the low-degree-first strategy has the most outstanding performance in the robustness test. The low-degree-first strategy was used to optimize the ecological network of the study area, 43 ecological corridors are added. After the optimization, the large and the small ecological corridors are evenly distributed to form a complete network, the optimized ecological network will be significantly more connected, resilient, and resistant to interference, the ecological flow transmission will be more efficient.

Controllability robustness of heat exchanger network based on complex network theory

2021 ◽  
Author(s):  
Zheng Wang ◽  
Ran Dong ◽  
Yunqing Dong ◽  
Huapeng Li ◽  
Ruijie Liu ◽  
...  
Keyword(s):  
Heat Exchanger ◽  
Complex Network ◽  
Network Theory ◽  
Heat Exchanger Network ◽  
Complex Network Theory

scholarly journals Extracting Correlations in Earthquake Time Series Using Visibility Graph Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Sumanta Kundu ◽  
Anca Opris ◽  
Yohei Yukutake ◽  
Takahiro Hatano
Keyword(s):  
Time Series ◽  
Complex Network ◽  
Recent Observation ◽  
Visibility Graph ◽  
Graph Analysis ◽  
Common Belief ◽  
Complex Network Theory ◽  
Event Time ◽  
Visibility Graph Analysis ◽  
Present Understanding

Recent observation studies have revealed that earthquakes are classified into several different categories. Each category might be characterized by the unique statistical feature in the time series, but the present understanding is still limited due to their non-linear and non-stationary nature. Here we utilize complex network theory to shed new light on the statistical properties of earthquake time series. We investigate two kinds of time series, which are magnitude and inter-event time (IET), for three different categories of earthquakes: regular earthquakes, earthquake swarms, and tectonic tremors. Following the criterion of visibility graph, earthquake time series are mapped into a complex network by considering each seismic event as a node and determining the links. As opposed to the current common belief, it is found that the magnitude time series are not statistically equivalent to random time series. The IET series exhibit correlations similar to fractional Brownian motion for all the categories of earthquakes. Furthermore, we show that the time series of three different categories of earthquakes can be distinguished by the topology of the associated visibility graph. Analysis on the assortativity coefficient also reveals that the swarms are more intermittent than the tremors.

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