Modeling and Key Technologies of a Data-Driven Smart City System

Fang, Yufei; Shan, Zhiguang; Wang, Wei

doi:10.1109/access.2021.3091716

Cited by 23 publications

(15 citation statements)

References 49 publications

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“…e spread reflects the typical characteristics of traditional banks. In financial auditing, you can pay more attention to assets and liabilities than the capital adequacy ratio so as to avoid excessive debt ratios causing excessive financial burdens and agency costs to financial institutions [23]. Taking into account the inevitable high debt ratio of banks, insurance financial institutions should pay more attention to the risk factors of asset-liability ratio.…”

Section: Summary Of Experimental Resultsmentioning

confidence: 99%

Data-Driven Intelligent Risk System in the Process of Financial Audit

Xie¹,

Zhang²

2022

Mathematical Problems in Engineering

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Financial auditing is an important part of government control, and monitoring the risks of the financial system helps maintain the stability of a country’s financial system. This paper aims to study the operation of data-driven intelligent risk analysis system in the process of financial auditing. When the risk level of the financial system reaches a certain warning point, it needs to be adjusted, conduct strict audits on high-risk institutions, strengthen cooperation with financial audit institutions, and make them more systematic. Risk control within a reasonable range will neither have a significant impact on the financial system nor increase the impact on the industry. This paper proposes to integrate the internal and establish an internal control system for the financial system.. If the internal control of the financial system cannot be sustained, financial innovation will cause great damage to financial institutions if the compensation is not good. Especially in terms of access strategy, it has made a strong contribution to economic innovation. The experimental data in this paper show that more than 25% of data-driven intelligent risk analysis systems have begun to be used in the process of financial auditing. At the same time, its utilization rate is significantly increasing with the development of technology. This paper introduces the relevant content of financial auditing, analyzes the auditing systems in different fields, integrates resources, taps on multisectoral needs, establishes a cross-departmental governance system, and improves financial stability and the efficiency of a wide range of social services.

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Section: Summary Of Experimental Resultsmentioning

confidence: 99%

Data-Driven Intelligent Risk System in the Process of Financial Audit

Xie¹,

Zhang²

2022

Mathematical Problems in Engineering

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“…Top-level design is a comprehensive and systematic planning from a macro perspective covering design idea, design goal, design environment, design process, design content, design method and quality inspection of the design results. This method is based on scientific and explicit ideas and featured with comprehensiveness and systematization, and thus can effectively guide and promote various social, economic and engineering works (Fang et al, 2021). Nevertheless, from the experience and lessons of previous smart city construction, the top-level design approach has also shown its limitations.…”

Section: Methodological Levelmentioning

confidence: 99%

A systematic framework for the complex system engineering of city data governance

et al. 2022

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The importance of data governance in the information age has become a deep consensus among all sectors. Under this context, data-driven urban governance has also become a key requirement for city development. However, as smart city and digital government continuously make progress, the utilization of urban data is still far from true intelligence, and no theoretical research on city data governance can fully guide the concrete implementation of engineering practice. In view of this, this paper proposes a systematic framework for the complex system engineering of urban data governance. We deconstruct urban data governance into a series of basic elements and discuss the key problems in urban data governance engineering regarding three dimensions, i.e., data quality, value and security. In view of the complexity of engineering projects, we establish the systematic framework of urban data governance from four levels, i.e., cognitive, methodological, technical and practical, and demonstrated the application in real practice with a case study on data-based epidemic prevention and control project in Shenzhen. The framework is proposed aiming to break through the key common difficulties in the practice of urban data governance engineering, provide systematic and operable solutions, and finally achieve the set goals.

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“…First, the accuracy and the automation level of existing methods regarding the data collection for CIM are still very limited, owing to the complex nature and large geographical areas of cities [81]. For example, how can we accurately obtain a high-fidelity 3D model of a city?…”

Section: Technical Issuesmentioning

confidence: 99%

City Information Modeling: State of the Art

et al. 2021

Applied Sciences

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The concept of city information modeling (CIM) has become increasingly popular in recent years. A literature review of previous CIM studies is presented in this paper. First, a bibliometric analysis of the current global CIM research is described, revealing that CIM has become a significant research hotspot. Next, three main research areas of the current CIM technique, namely data collection, integration, and visualization, are summarized to describe the characteristics of CIM research. Furthermore, some widely used CIM platforms are compared, and typical application cases of the CIM technique at different stages of the city life cycle are summarized. Finally, the current issues in CIM research are discussed, and future development directions are proposed. The findings of this study are expected to help researchers understand the current state of CIM and identify future development directions, thereby promoting CIM research development.

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Modeling and Key Technologies of a Data-Driven Smart City System

Cited by 23 publications

References 49 publications

Data-Driven Intelligent Risk System in the Process of Financial Audit

Data-Driven Intelligent Risk System in the Process of Financial Audit

A systematic framework for the complex system engineering of city data governance

City Information Modeling: State of the Art

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