Prediction of GDP in Time Series Data Based on Neural Network Model

Jingui Wu, Y. He
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引用次数: 4

Abstract

Gross domestic product(GDP) is an important macro index to measure a country's national strength. As a typical time series data, it has certain rules. Therefore, this paper analyzes and processes the GDP data from 1980 to 2020 based on Matlab2014b software and Excel software. The program of BP neural network is written to predict the GDP value of China in the next 5 years (2021–2025). Through the operation of the model, this paper obtains the predicted value of China in the future 5. The results show that the GDP value of China in the future is still in a rising stage, which is consistent with the historical trend. Therefore, it is effective to use neural network model to forecast GDP of time series data.
基于神经网络模型的时间序列GDP预测
国内生产总值(GDP)是衡量一个国家国力的重要宏观指标。作为典型的时间序列数据,它有一定的规律。因此,本文利用Matlab2014b软件和Excel软件对1980 - 2020年的GDP数据进行分析和处理。编写BP神经网络程序,预测中国未来5年(2021-2025)的GDP值。通过对模型的操作,本文得到了中国未来经济的预测值。结果表明,未来中国GDP价值仍处于上升阶段,与历史趋势一致。因此,利用神经网络模型对时间序列数据的GDP进行预测是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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