Theoretical Approach for Evaluating the Connectivity of Distributed Systems and Telecommunications for the Digital Economy

Chizhikov, E. N.; Gorbunov, A. A.; Белов, А. С.; Trakhinin, E. L.; Stavitskii, D. V.

doi:10.3103/s0146411621080356

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…Wang et al discussed the role of the digital economy in green innovation and put forward relevant suggestions for improving geographic information capabilities [3]. Chizhikov et al considered a theoretical approach that made it possible to formulate rational choices for the construction of distributed systems and telecommunications in the digital economy under the influence of external special software and hardware [4]. On the basis of measuring the level of data economy at the city level, combined with pm2.5 data of haze pollution and related economic statistics, Huang discussed the relationship between the development level of digital economy and urban haze pollution from both theoretical and empirical levels [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of High-quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm

Wang

2022

International Transactions on Electrical Energy Systems

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With the strong development of industrial transformation, the digital economy, as the most dynamic, innovative, and widely radiated economic form at present, has become an important force driving the development of the global economy. Shaanxi Province has accelerated the development of the digital economy, and the development of the province’s digital economy has shown a good trend. However, the current digital economy development measurement is still unable to accurately observe the development law of the digital economy industry, which makes it difficult to measure the control standards for the digital economy industry. Therefore, this study has evaluated the development of digital economy in Shaanxi Province based on machine learning algorithms. This study first puts forward the dimensions of digital economy monitoring and evaluation and then combines the characteristics of digital economy development in Shaanxi Province to determine the quality evaluation indicators of digital economy development. Finally, according to the machine learning algorithm, a quality evaluation model of digital economy development was established, and through the evaluation results, suggestions were put forward for the development plan of digital economy in Shaanxi Province. The experimental results showed that, after re-planning the digital economy in Shaanxi Province according to the evaluation results, the development of the digital economy in Shaanxi Province has increased by 9.82%, indicating that the evaluation model plays a good reference role in the formulation of the digital economy development plan.

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Section: Introductionmentioning

confidence: 99%

Evaluation of High-quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm

Wang

2022

International Transactions on Electrical Energy Systems

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“…The rapid development of the digital economy has led to the emergence of the platform economy as a new form of industrial organization [18][19]. However, with the rapid development of internet platforms, their market structure has gradually evolved into a competitive effect: the winner takes all, and the stronger would become stronger.…”

Section: Digital Economymentioning

confidence: 99%

Multi Factor Risk Assessment Algorithm in Digital Economy Platform

Zhao,

Cao,

Mei

2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

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With the rapid development of the digital economy, the platform economy has become an important component of today's society. A digital economy platform refers to a form of economic activity that conducts transactions and provides services through online platforms. The platform economy has advantages such as efficiency, convenience, and openness, but it also faces risks such as data security, user privacy, and market competition. Therefore, how to effectively evaluate and manage risks in the platform economy has become an important issue in the field of digital economy. This article aimed to explore the application of multi factor risk assessment algorithms in digital economy platforms, in order to improve the risk management level of the platform and promote the healthy development of the platform economy. This article conducted research on user risk, internal risk, transaction risk assessment, and data security risk assessment. Through algorithm comparison and investigation, relevant data on internet digital platforms were obtained and the performance of evaluation algorithms was evaluated. Experimental data showed that the Relief algorithm performs best in enterprise competition risk classification, with an accuracy of 80% in data security, 79% in user trust, 84% in legal and regulatory accuracy, and 85% in talent and technology accuracy.

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Theoretical Approach for Evaluating the Connectivity of Distributed Systems and Telecommunications for the Digital Economy

Cited by 2 publications

References 4 publications

Evaluation of High-quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm

Evaluation of High-quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm

Multi Factor Risk Assessment Algorithm in Digital Economy Platform

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