Security Management System Construction of Information System Based on Big Data Analysis

Li, Kunying; Ding, Yu; Li, Xiaolian; He, Xu; Zhang, Wenting; Li, Wenling

doi:10.1109/icuems50872.2020.00120

Cited by 2 publications

(2 citation statements)

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“…In the international and domestic context of curbing global warming and promoting the optimization of urban spatial structure, controlling the expansion of carbon emissions due to urban sprawl has become a crucial strategy for building sustainable cities and achieving the "dual-carbon" goal. As for the Yangtze River Basin, current research primarily focuses on the impacts of urban sprawl on environmental pollution and factors of production, with less emphasis on the effects on carbon emission intensity (Li et al, 2021;Li & Tang, 2023;Guan et al, 2024). Therefore, this study explores the effect of urban sprawl on carbon emission intensity in the Yangtze River Basin on the basis of outlining the spatial and temporal patterns of urban sprawl and carbon emission intensity in the Yangtze River Basin.…”

Section: Introductionmentioning

confidence: 99%

Empirical Analysis of the Impact of Urban Sprawl on Carbon Emission Intensity of Cities in the Yangtze River Basin

Jiang,

Xu,

Zhao

et al. 2024

Preprint

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This paper constructs an urban sprawl index (USI) based on nighttime lighting data, and explores the impact of urban sprawl on carbon emission intensity (CEI) using panel data model and spatial econometric model. The results show that: (1) In the correlation test between the USI constructed based on nighttime lighting data and the USI constructed from statistical data, most models yield significantly positive results. The USI constructed from nighttime lighting data can be used to characterize urban sprawl. (2) The USI and CEI in the Yangtze River Basin decreased overall. The distance between CEI and USI exhibited a general trend of widening, leading to a gradual weakening of the influence between the two. In spatial distribution, the USI experienced minimal change overall, whereas the second-highest intensity of CEI was notably concentrated towards the lower reaches of the Yangtze River. (3) There is a significant U-shaped relationship and spillover effect between CEI and USI. The impact of the level of economic development and the extent of greening is more pronounced, while the influence of other variables is relatively minor. The results of the study suggest that spatial planning should be tailored to the local economic development status. It is important to leverage the benefits of population agglomeration to enhance the capacity of urban ecological resources and encourage sustainable production practices in cities within the Yangtze River Basin.

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Section: Introductionmentioning

confidence: 99%

Empirical Analysis of the Impact of Urban Sprawl on Carbon Emission Intensity of Cities in the Yangtze River Basin

Jiang,

Xu,

Zhao

et al. 2024

Preprint

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“…The establishment of a technical system framework for smart cities based on big data technology is discussed, and the feasibility of this technical system framework is explored. The literature [23] outlines the significance of machine learning modeling techniques in the construction of smart cities. Its important role in further promoting the development of the Zhengzhou Airliner Economic Zone in China and the whole process is analyzed.…”

Section: Introductionmentioning

confidence: 99%

A strategy for building a smart sports platform based on machine learning models

Gong¹

2023

3C TIC

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With the rapid development of big data technology, it has greatly changed the way people get information, and also improved the speed and quality of information. In this context, smart sports has become a new trend in sports development. This paper creates an intelligent learning environment and builds a smart sports platform through advanced concepts and technical means, which can effectively optimize the integration and sharing of sports resources. Starting from the overall architecture design of smart sports, the key technologies of machine learning model to realize smart sports are sorted out. Through the five basic linking stages with machine learning model as the core, the value innovation path of platform construction structure is analyzed. The current status of sports resources application is studied, and the data mining algorithm is used to calculate the user usage data of the smart sports platform and improve the construction of the smart platform. Through the construction of the smart sports platform, people shift from traditional reading books and watching TV programs to getting information through intelligent mobile terminals, and the proportion of attention to sports information is as high as 58.6%. This shows that by building a smart sports platform, it can provide support and guarantee for the sustainable development of sports.

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Security Management System Construction of Information System Based on Big Data Analysis

Cited by 2 publications

References 1 publication

Empirical Analysis of the Impact of Urban Sprawl on Carbon Emission Intensity of Cities in the Yangtze River Basin

Empirical Analysis of the Impact of Urban Sprawl on Carbon Emission Intensity of Cities in the Yangtze River Basin

A strategy for building a smart sports platform based on machine learning models

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