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

      1
      International Transactions on Electrical Energy Systems
      Hindawi Limited

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          Abstract

          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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          MapReduce-based big data classification model using feature subset selection and hyperparameter tuned deep belief network

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            Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes

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                Author and article information

                Contributors
                Journal
                International Transactions on Electrical Energy Systems
                International Transactions on Electrical Energy Systems
                Hindawi Limited
                2050-7038
                October 4 2022
                October 4 2022
                : 2022
                : 1-9
                Affiliations
                [1 ]Business College, Xi’an Siyuan University, Xi’an 123456, Shaanxi, China
                Article
                10.1155/2022/6327347
                a0d701be-2b1a-4d64-b293-7f7acc8c2fa7
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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