A Study on the Spatial Structure of the Bu-Ul-Gyeong Megacity Using the City Network Paradigm

Castells proposed that “space of flow” has multiple layers, and considered that transportation infrastructure is the carrier of its formation. However, few studies have focused on whether the infrastructure behind factor flows can provide sufficient support. In this paper, the basic supporting role of traffic networks in regional factor flows is examined. Firstly, we use traffic-connection data, enterprise-investment data and human-flow data to build a traffic network, enterprise-association network and inter-city-trip network, respectively. Then, we construct fitting models of the traffic network and the other two networks from two aspects: centrality and connection degree. Finally, this paper analyzes the standard residuals of the fitting results and looks for outliers that are greater than 1.65 or less than −1.65. Through outliers, we can find out where the traffic network cannot support the inter-city factor flows, and where the traffic network is too developed. The conclusions are as follows: First, the immaterial capital flows are still affected by the connectivity of transport facilities. With an improvement in traffic conditions, the capital links between cities can be enhanced correspondingly. Therefore, cities can gather more capital. Second, the attraction and radiation power of high-grade cities in terms of both human and capital flows are far beyond the traffic condition. They also motivate the neighboring cities to form a scale of capital- and human-flow connection that exceeds the average traffic conditions of the whole province. By analyzing the relationship between factor flows and infrastructure, and identifying mismatched networks, this paper will be helpful in many regards. It can provide guidance for Zhejiang Province in formulating transportation strategies. In addition, the conclusions can also provide decision-making support for optimizing regional infrastructure construction.

Section: Literature Review 21 Development Of Urban Network Researchmentioning

confidence: 99%

Section: Literature Review 21 Development Of Urban Network Researchmentioning

confidence: 99%

Validation of the Basic Supporting Role of Traffic Networks in Regional Factor Flow: A Case Study of Zhejiang Province

Ding

Wang

et al. 2023

“…The new generation of application scenarios such as We Media era, new video conference, mobile teaching, AR, VR, meta universe, etc., also makes the number of intelligent terminals show an explosive growth trend [3,4]. According to the statistics, it is estimated that, in 2040, the number of intelligent terminal connections will increase by more than 30 times compared with 2022, and the average monthly traffic will increase by more than 130 times [5]. Finally, in the 6G era, there will be an Internet market of "hundreds the whole wireless communication system and reduces the computing pressure of the base station to a certain extent, while improving the spectrum resource utilization and throughput of the system [11].…”

Section: Introductionmentioning

confidence: 99%

D2D Communication Network Interference Coordination Scheme Based on Improved Stackelberg

Chen

et al. 2023

The sudden explosive growth of data in intelligent devices and existing communication networks has brought great challenges to existing communication networks. On the one hand, D2D (device to device) technology greatly improves the utilization of spectrum resources; on the other hand, it improves the communication quality of users. It has become an important part of the future communication network. Aiming at the problem that the existing D2D communication network system has complex user interference, and the communication quality of cellular users is difficult to guarantee, a D2D communication network interference coordination scheme based on improved Stackelberg is proposed. Using resource allocation and power control to solve the interference coordination problem, this paper proposes an improved Stackelberg model based on DQN (deep Q network), establishes the master–slave game between cellular users and multiplexing resource users (D2D users; relay communication users), optimizes the cost parameters in the Stackelberg mode and improves the transmission power and resource allocation scheme of multiplexing resource users. The simulation results show that compared with similar algorithms, the algorithm proposed in this paper has the best performance in guaranteeing the QoS of cellular users in the system and has good interference management capability for D2D communication networks.

“…The spatial structure of urban networks, as a spatial distribution pattern resulting from the interactions among urban nodes [17], emphasizes the horizontal and complementary integration between urban regions based on the establishment of transportation networks and intercity complementarity [10,18]. The urban network paradigm is aligned with the functional perspective of a multi-centered spatial structure, as it highlights the functional connections and interactions among multiple central regions within urban regions [19].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, some studies have analyzed the community structure of integrated regions through the lens of urban network theory. For example, Baek and Joo [19] analyzed the regional centrality of the Bu-Ul-Gyeong (BUG) megacity at various spatial scales using mobile flow data from 2019 to 2020.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Construction Networks and Structural Characteristics of Pearl River Delta and Surrounding Cities Based on Multiple Connections

Nie

2023

The Pearl River Delta (PRD) is one of three world-class city clusters in China, which is important for the strategical deployment of the national “Belt and Road”. Based on nighttime lighting data, Baidu index, and train stopping times, this study analyzed the network of spatial patterns and structural evolution of the PRD and surrounding cities via social network analysis and dynamic network visualization, providing new perspectives and ideas for the study of intercity linkages and urban networks. The results provide decision support to the government for urban cluster planning. From 2014 to 2020, the economic network evolved from a uniaxial structure to an “inverted V” structure. The transportation network evolved from a uniaxial structure to a “△” structure. The information network did not show any obvious structural changes during its development, except for a star-shaped radial structure. The PRD city cluster and its surrounding cities exhibited a spatially non-uniform distribution in terms of spatial connections. The total connections between Guangzhou and Foshan and the surrounding cities in terms of economic, transportation, and information functions account for 30%, 28%, and 10% of the total urban connections, respectively. The graph entropy growth rates of the PRD city cluster and surrounding cities in economic, transportation, and information networks from 2014 to 2020 were 39.9%, 115.4%, and 5.1%, respectively. The network structures of economic and transportation networks stabilized eventually. The information network structures are stable.