Industry structure optimization via the complex network of industry space: A case study of Jiangxi Province in China

Cheng, Jing; Xie, Yang; Zhang, Jie

doi:10.1016/j.jclepro.2022.130602

Cited by 23 publications

(11 citation statements)

References 43 publications

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“…Yang et al, quantified the spatial distribution of information services and its sub-industries in Beijing in 2008 and 2013, and examined the spatial path dependence by using standard deviation ellipse and back propagation neural network algorithm [35]. Cheng et al, studied the optimization of industrial structure in Jiangxi Province of China using complex network of industrial space [2].…”

Section: Literature Reviewmentioning

confidence: 99%

“…From calculating Equation (1), the dominant urban functions of every district in Shenzhen are obtained. Based on the dominant urban functions, the interdependencies between Mathematics 2022, 10, 2412 9 of 20 two urban functions can be computed by Equation (2). The results of the interdependencies between the urban functions before and under the lockdown of COVID-19 are shown in Table 2.…”

Section: Interdependency Between the Urban Functionsmentioning

confidence: 99%

“…Due to the influences of COVID-19 on the world, it is very important to study the urban functions of a megacity under the lockdown of COVID-19. The complex network is an effective approach to analyze the changes and renewal of the urban functions of a city [2].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the Complex Network of the Urban Function under the Lockdown of COVID-19: Evidence from Shenzhen in China

Cheng

Yin

2022

Mathematics

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In this paper, the complex network of the urban functions in Shenzhen of China under the lockdown of the corona virus disease 2019 (COVID-19) is studied. The location quotient is used to obtain the dominant urban functions of the districts in Shenzhen before and under the lockdown of COVID-19. By using the conditional probability, the interdependencies between the urban functions are proposed to obtain the complex networks of urban functions and their clusters. The relationships between the urban functions, and the overall and cluster characteristics of the urban functions before and under the lockdown of COVID-19 are analyzed based on the complex networks. The mean degree and mean weighted degree of the primary categories of the urban functions are obtained to discuss the classification characteristics of the urban functions before and under the lockdown of COVID-19. Then, the differences and changes of the urban functions before and under the lockdown of COVID-19 are compared, and the corresponding policy implications under the lockdown of COVID-19 are presented. The results show that under the lockdown of COVID-19, the correlation of the urban functions is stronger than that before the lockdown; the common urban functions are more useful and essential, and finance, fine food and medical treatment are important; public service and government departments have the most positive relationship with other urban functions, and finance service has the highest spatial agglomeration distribution trend; and the cluster characteristics of urban functions are more related to people’s livelihood, and the urban functions show incomplete and cannot be operated for long term.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Interdependency Between the Urban Functionsmentioning

confidence: 99%

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Analysis of the Complex Network of the Urban Function under the Lockdown of COVID-19: Evidence from Shenzhen in China

Cheng

Yin

2022

Mathematics

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“…Based on various construction methods of approximation functions or various discrete methods of the problem to be solved, many meshless methods have been proposed [10][11][12][13][14]. The ordinary leastsquares (OLS) method is the best approximation [15], and it has been applied in engineering fields widely [16,17]. Based on the OLS method, Lancaster et al presented the moving least-squares method (MLS) approximation [18], which is one of the common methods used to construct approximation functions and has a wide range of applications in meshless [18].…”

Section: Introductionmentioning

confidence: 99%

A Dimension-Splitting Variational Multiscale Element-Free Galerkin Method for Three-Dimensional Singularly Perturbed Convection-Diffusion Problems

Wang¹,

Wu²,

Xu³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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By introducing the dimensional splitting (DS) method into the multiscale interpolating element-free Galerkin (VMIEFG) method, a dimension-splitting multiscale interpolating element-free Galerkin (DS-VMIEFG) method is proposed for three-dimensional (3D) singular perturbed convection-diffusion (SPCD) problems. In the DS-VMIEFG method, the 3D problem is decomposed into a series of 2D problems by the DS method, and the discrete equations on the 2D splitting surface are obtained by the VMIEFG method. The improved interpolation-type moving least squares (IIMLS) method is used to construct shape functions in the weak form and to combine 2D discrete equations into a global system of discrete equations for the three-dimensional SPCD problems. The solved numerical example verifies the effectiveness of the method in this paper for the 3D SPCD problems. The numerical solution will gradually converge to the analytical solution with the increase in the number of nodes. For extremely small singular diffusion coefficients, the numerical solution will avoid numerical oscillation and has high computational stability. KEYWORDSDimension-splitting multiscale interpolating element-free Galerkin (DS-VMIEFG) method; interpolating variational multiscale element-free Galerkin (VMIEFG) method; dimension splitting method; singularly perturbed convection-diffusion problems

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“…As a kind of soft material, the large deformation of hydrogel is very complicated [19]. With the developments of deep learning and data analysis, complex network has been applied in many fields in science and engineering [20]. In the paper submitted to this Special Issue by Zhu et al [21], based on the complex network structure of hydrogel with inhomogeneous and random distribution of polymer chains, a deep learning approach to predict the mechanical properties of hydrogels from polymer network structures is presented.…”

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confidence: 99%

Preface to the Special Issue on “Numerical Computation, Data Analysis and Software in Mathematics and Engineering”

Cheng

2022

Mathematics

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Industry structure optimization via the complex network of industry space: A case study of Jiangxi Province in China

Cited by 23 publications

References 43 publications

Analysis of the Complex Network of the Urban Function under the Lockdown of COVID-19: Evidence from Shenzhen in China

Analysis of the Complex Network of the Urban Function under the Lockdown of COVID-19: Evidence from Shenzhen in China

A Dimension-Splitting Variational Multiscale Element-Free Galerkin Method for Three-Dimensional Singularly Perturbed Convection-Diffusion Problems

Preface to the Special Issue on “Numerical Computation, Data Analysis and Software in Mathematics and Engineering”

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