China’s Economic Forecast Based on Machine Learning and Quantitative Easing

Qiu, Chang

doi:10.1155/2022/2404174

Cited by 2 publications

(1 citation statement)

References 20 publications

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“…Nevertheless, the forecasting approach also has some limitations, all the forecasting models are linear forecasting, which is an important way to forecast GDP, and although it has higher accuracy compared with the traditional forecasting approach, the validity has to continue to be improved [18]. is study was carried out on the basis of others' studies, choosing nonlinear structural models and relevant indicators for forecasting, counting GDP values, and comparing different forecasting results to confirm the validity and feasibility of the forecasting results [19,20].…”

Section: Analysis Of Prediction Accuracymentioning

confidence: 99%

Socioeconomic Development Trend Prediction Model and Research Which is Based on Deep Neural Network

Zhang

Wei²,

Wang³

2022

Mathematical Problems in Engineering

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In recent years, my country’s economic development has entered a new stage, and economic development has entered a new height. Gross Domestic Product (GDP) is the most important and commonly used measure to evaluate social and economic development. It can comprehensively reflect the operating conditions of the economy. At the 2014 APEC summit, Xi Jinping focused on the characteristics of the new normal of China’s economy. The economic growth has undergone major changes, and the economic structure has become more and more complete and has been continuously optimized. Therefore, the driving force of innovation plays an important role in the future social and economic development. The high-tech demonstration zone is the main hub of my country’s economic innovation and scientific and technological progress, and the development of the high-tech demonstration zone is particularly important in the development of the innovative economy. By predicting the economic growth, the development structure can be adjusted in time, and the coordinated allocation of resources can be achieved, which is conducive to the stable and rapid development of the economy. Therefore, it is very necessary to predict my country’s economic growth. At present, more and more scholars have invested more energy in the establishment of economic forecasting models. Previously, the prediction effect of traditional models was not satisfactory. At present, the field of target camera machine learning has been transferred. The application of the powerful nonlinear fitting ability of the machine learning model can improve the prediction effect. Based on this, this paper studies the use of artificial neural network with improved BP algorithm to predict social and economic development, and analyzes social and economic development trends and changing laws. The results show that the forecasting model constructed in this paper has a good forecasting effect, and the research results can provide a theoretical basis for scientifically formulating macro-control policies.

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Section: Analysis Of Prediction Accuracymentioning

confidence: 99%

Socioeconomic Development Trend Prediction Model and Research Which is Based on Deep Neural Network

Zhang

Wei²,

Wang³

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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Forecasting of Export Volume Using Artificial Intelligence Based Algorithms

Özden

2022

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

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Technological breakthroughs have transformed communication and taken transportation, health, and commerce to an unprecedented level. In this way, sudden developments have rapidly affected all countries. In this context, analysis methods are changing compared to the past, and annual analyses fail to catch the trend even for macroeconomic indicators. In this paper, new artificial intelligence-based estimation methods were used to see the future trend of export volume, and their estimation performances were compared by adding them to the classical econometric method. Historical quarterly data from 2013 to 2021 were used in the training and testing phases of the models. For this purpose, the variables of gross domestic product, foreign direct investment, and dollar exchange rate, which affect the export volume, were determined as inputs in estimating the export volume. According to the analysis results, support vector machine model for predicting export volume in Turkey. This study can provide an essential basis for policymakers to export estimation and formulate their export-enhancing policies effectively.

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China’s Economic Forecast Based on Machine Learning and Quantitative Easing

Cited by 2 publications

References 20 publications

Socioeconomic Development Trend Prediction Model and Research Which is Based on Deep Neural Network

Socioeconomic Development Trend Prediction Model and Research Which is Based on Deep Neural Network

Forecasting of Export Volume Using Artificial Intelligence Based Algorithms

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