Complex networks and integrated centrality measure to assess the importance of streamflow stations in a River basin

Joo, Hongjun; Kim, Hung Soo; Sivakumar, Bellie

doi:10.1016/j.jhydrol.2021.126280

Cited by 17 publications

(13 citation statements)

References 23 publications

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“…A keyword has a higher closeness score when the sum of its distances to all the other keywords in a network is lower. This means that the keyword with the highest closeness value has the shortest connection distances to all the other keywords in the network (Joo et al 2021). It can be seen from Figure 2 that "ethics" (betweenness centrality score: 0.22; closeness centrality score: 0.24) is located at the center of the network and connect other keywords.…”

Section: The Relationship Among Hot Research Topicsmentioning

confidence: 93%

Where the Research Interests of Graduate Students in China’s Christian Universities Lie

2021

Religions

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Focusing on the research landscape for graduate students of China’s Christian universities is of great significance for making sense of the path along which the theological and practical studies are conducted by contemporary China’s Christian universities and for promoting the dialogue and understanding between Chinese and foreign seminaries. In this research, thesis topics selected by graduate students majoring in theology are classified into four categories: universal theoretical research, universal practical research, theoretical research of Chinese Christianity, and practical research of Chinese Christianity. Results of coded categorical data analysis and case study show that graduate students mainly focus on universal theories without giving adequate attention to the topic of the “Sinification” of Christianity. In their universal theoretical research, graduate students examine classic Christian works and theological thoughts of important figures in a detailed and in-depth way. Universal practical studies are skewed to practices of religious reforms and teaching improvements from a multidisciplinary perspective. In the theoretical research of Sinified Christianity, researchers build upon the commensurability between traditional Chinese culture and Christian theology, including the theological thoughts of important Christian figures in China, to explore the fulfillment of cultural, national, and social identities. In the practical research of Christianity in China, empirical methodologies are widely applied, centering on the “localization” process and forms of practices taking place in churches of China. The coincidentia oppositorum between universality and particularity dictates that much tension exists with respect to the development of Christianity in China. Focusing on the accommodative process between universality and particularity is important to produce further implications for research to be conducted by China’s Christian universities.

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Section: The Relationship Among Hot Research Topicsmentioning

confidence: 93%

Where the Research Interests of Graduate Students in China’s Christian Universities Lie

2021

Religions

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“…The complex network is an effective method for representing the structure and process of a complex and fluid hydrological system [45,46]. The network (or graph) consists of multiple nodes and links.…”

Section: Complex Networkmentioning

confidence: 99%

“…cess of a complex and fluid hydrological system [45,46]. The network (or graph) consists of multiple nodes and links.…”

Section: Complex Networkmentioning

confidence: 99%

Improvement of Deep Learning Models for River Water Level Prediction Using Complex Network Method

Kim

Han²,

Wang

et al. 2022

Water

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Accurate water level prediction is one of the important challenges in various fields such as hydrology, natural disasters, and water resources management studies. In this study, a deep neural network and a long short-term memory model were applied for water level predictions between 2000 and 2020 in the Phan Rang River Basin of Nihn Thuan located in Vietnam. In addition, a complex network model was utilized to improve the predictive ability of both models for water level prediction at the outlet point of the basin. The water level prediction by each model was compared with the observed water level data, and the predictive power for each model was evaluated using three statistical metrics: the correlation coefficient (CC), the Nash–Sutcliffe efficiency coefficient (NSE), and the normalized root-mean-squared error (NRMSE). Using all data from nearby stations, there may be distortions in the prediction due to unnecessary data for model learning. Therefore, the complex network method was applied to find best data sources providing factors contributing to water level behaviors. The results of this study showed that a combination of the long short-term memory model and the complex network provided the best predictive performance (CC: 0.99; NSE: 0.99; and NRMSE: 0.17) and was selected as the optimal model for water level prediction in this study. As the need for disaster management is gradually increasing, it is expected that the deep learning model with the complex network method have sufficient potential to reduce the damage from natural disasters and improve disaster response systems, such as in the outskirts of Vietnam.

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“…It analyzes the behavior of individuals in the system and the connections between individuals from the perspective of the system as a whole. This method had been widely used in the study of energy trade patterns [21], waste management [22], carbon dioxide emission [23], ecosystem management [24], transportation [25], and urban planning [15], etc. Many scholars have used complex network models to study land use change as well [15,21,26,27], from the perspective of the system as a whole, to identify the key land use types and evaluate the stability of the land use system.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Change of Land Use in a Coastal Reclamation Area: A Complex Network Approach

Liu

Kong

et al. 2021

Sustainability

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Coastal ecological protection and restoration projects aimed to restore and recover the ecological environment of coastal wetland with high-intensity human reclamation activity, while the integrity of the coastal wetland system with human reclamation activity and the ability of individual land use types to control the overall system were not fully considered. In this study, a six-stage land use conversion network was constructed by using a complex network model to analyze coastal land use dynamic changes in the coastal reclamation area located in eastern China from 1977 to 2016. The results showed that land use types had gradually transformed from being dominated by natural types to artificial types, and the speed of transformation was accelerating. The proportion of un-reclaimed area decreased from 93% in 1977 to 46% in 2007, and finally fell to 8% in 2014 and 2016. Tidal flat and halophytic vegetation were the main output land use types, while cropland, woodland and aquaculture pond were the main input land use types. Cropland had the highest value of betweenness centrality, which played a key role in land use change from 1992 to 2014. The land use system of the coastal reclamation area was the most stable in 2002–2007, followed by 1984–1992, and the most unstable in 2007–2014. The Chinese and local government should carry out some measures to improve the land use in coastal wetland ecosystems, including the allocation and integration of land use for production space, living space, and ecological space, and develop multi-functionality of land use to realize the coastal high-quality development and coastal ecological protection and restoration.

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Complex networks and integrated centrality measure to assess the importance of streamflow stations in a River basin

Cited by 17 publications

References 23 publications

Where the Research Interests of Graduate Students in China’s Christian Universities Lie

Where the Research Interests of Graduate Students in China’s Christian Universities Lie

Improvement of Deep Learning Models for River Water Level Prediction Using Complex Network Method

Spatio-Temporal Change of Land Use in a Coastal Reclamation Area: A Complex Network Approach

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