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<p>The digital economy is growing rapidly, and all recognize its enormous potential. Based on the ARIMA-LSTM-XGBoost hybrid model, this paper analyzes the current situation of digital economy empowering the high-quality development of manufacturing industry based on the economic development of Anhui Province from 2013 to 2020 and explores the logical turn and practical path of China’s high-quality economic development based on it. This paper first introduces ARIMA time series model, LSTM model and XGBoost model and constructs a hybrid ARIMA-LSTM-XGBoost model based on them. Secondly, we analyze the comprehensive index of high-quality development of manufacturing industry in Anhui Province as an example and research and analyze the level of high-quality development of manufacturing industry based on the ARIMA-LSTM-XGBoost hybrid model. The overall manufacturing high quality development composite index of Anhui province increased from 0.1648 in 2013 to 0.3543 in 2020. The four indicators of urbanization rate, financial development level, human resources and marketization level through significance level are -0.0004, -0.0008, 0.0037 and 0.2608, respectively. In summary, the digital economy is the logical turn for the current high-quality development of China’s economy.</p>
</abstract>

The digital economy is growing rapidly, and all recognize its enormous potential. Based on the ARIMA-LSTM-XGBoost hybrid model, this paper analyzes the current situation of digital economy empowering the high-quality development of manufacturing industry based on the economic development of Anhui Province from 2013 to 2020 and explores the logical turn and practical path of China’s high-quality economic development based on it. This paper first introduces ARIMA time series model, LSTM model and XGBoost model and constructs a hybrid ARIMA-LSTM-XGBoost model based on them. Secondly, we analyze the comprehensive index of high-quality development of manufacturing industry in Anhui Province as an example and research and analyze the level of high-quality development of manufacturing industry based on the ARIMA-LSTM-XGBoost hybrid model. The overall manufacturing high quality development composite index of Anhui province increased from 0.1648 in 2013 to 0.3543 in 2020. The four indicators of urbanization rate, financial development level, human resources and marketization level through significance level are -0.0004, -0.0008, 0.0037 and 0.2608, respectively. In summary, the digital economy is the logical turn for the current high-quality development of China’s economy.

Research on the Logical Turn and Practical Path of China’s High-Quality Economic Development in the Context of Digitalization

Nanjing University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The digital economy is growing rapidly, and all recognize its enormous potential. Based on the ARIMA-LSTM-XGBoost hybrid model, this paper analyzes the current...

Research on the Logical Turn and Practical Path of China’s High-Quality Economic Development in the Context of Digitalization

Online veröffentlicht: 02. Juni 2023

Seitenbereich: -

Eingereicht: 17. Apr. 2022

Akzeptiert: 17. Okt. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00167

Schlüsselwörter
ARIMA time series model, LSTM model, XGBoost model, Logistic steering, Practice path

© 2023 Xianwang Lv, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Logical Turn and Practical Path of China’s High-Quality Economic Development in the Context of Digitalization

Online veröffentlicht: 02. Juni 2023

Seitenbereich: -

Eingereicht: 17. Apr. 2022

Akzeptiert: 17. Okt. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00167

SchlüsselwörterARIMA time series model, LSTM model, XGBoost model, Logistic steering, Practice path

© 2023 Xianwang Lv, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
ARIMA time series model, LSTM model, XGBoost model, Logistic steering, Practice path