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A Study on the Application of BP Neural Network Based on Visual Recognition in Regional Economic Forecasting

机译:基于视觉识别的BP神经网络在区域经济预测中的应用研究

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摘要

The economic growth in the new normal is no longer limited to the total amount and scale of economic growth in the traditional and neoclassical periods, but has changed to “quality” and “development” under the dual requirements of historical changes and tasks of the times. The quality of regional economic growth is an important part of the quality of China’s economic development and an important part of the quality of China’s economic development in the new era. Therefore, this paper proposes a BP neural network based on visual recognition in a regional economic prediction model and conducts application experiments. This regional economic forecasting model is relying on data technology for economic panel data mining, then graphical processing of panel data, followed by the selection of visual recognition technology for economic panel map analysis, to derive its various component coefficients, and finally then using the BP neural network to fit the prediction, at the same time, through long-term and short-term prediction, to predict the future development quality of each region’s change trends and fluctuations, to predict the institution’s role, so as to avoid major transitions and deteriorating alarms, and to provide support for the macroregulation of regional economic development quality.
机译:新常态下的经济增长不再局限于传统时期和新古典时期经济增长的总量和规模,而是在历史变迁和时代任务的双重要求下,向“质量”和“发展”转变。区域经济增长的质量是我国经济发展质量的重要组成部分,是新时代我国经济发展质量的重要组成部分。因此,该文提出了一种基于视觉识别的区域经济预测模型中的BP神经网络,并进行了应用实验。该区域经济预测模型是依靠数据技术进行经济面板数据挖掘,然后对面板数据进行图形处理,然后选择视觉识别技术进行经济面板地图分析,推导出其各个分量系数,最后利用BP神经网络进行拟合预测,同时, 通过长期和短期预测,预测未来发展质量各区域的变化趋势和波动,预测机构的作用,从而避免重大转型和恶化警报,为区域经济发展质量的宏观调控提供支撑。

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