|
|
基于ARIMA模型的河北省GDP预测研究
|
Abstract:
本文采用MATLAB软件，对河北省1978~2022年国内生产总值(GDP)进行分析，选取1978~2018年数据作为训练集，选取2019~2022年数据作为测试集，最终创建了ARIMA(1, 2, 0)模型，并使用此模型预测了河北省未来四年即2023~2026年的地区生产总值。根据此模型，预测出河北省2023~2026年GDP分别为：48679.4亿元、52075.9亿元、55132.5亿元和58518.9亿元。最终计算平均预测误差为1.91%，发现该模型具有较好的预测精度，能够有效的预测河北省GDP。
This article uses MATLAB software to analyze the Gross Domestic Product (GDP) of Hebei Province from 1978 to 2022. The data from 1978 to 2018 is selected as the training set, and the data from 2019 to 2022 is selected as the test set. Finally, an ARIMA (1, 2, 0) model is created, and this model is used to predict the regional GDP of Hebei Province in the next four years, namely 2023~2026. According to this model, it is predicted that the GDP of Hebei Province from 2023 to 2026 will be 48679.4 billion yuan, 52075.9 billion yuan, 55132.5 billion yuan, and 5851.89 billion yuan, respec-tively. The final average prediction error is 1.91%, indicating that the model has good prediction accuracy and can effectively predict the GDP of Hebei Province.
| [1] | 于涧, 马涛, 于泽翔, 等. 基于BP神经网络的河北省GDP预测研究[J]. 北方工业大学学报, 2024, 36(3): 126-130. |
| [2] | 陈满丽, 张慧娟, 焦楠楠, 等. 基于MATLAB的ARIMA模型对我国GDP预测的研究[J]. 中国市场, 2024(12): 1-4. |
| [3] | 殷佳棋. 内蒙古自治区GDP分析与预测[J]. 内蒙古科技与经济, 2024(7): 15-18, 54. |
| [4] | 肖丹. 基于ARIMA模型的四川省GDP分析与预测[J]. 生产力研究, 2023(10): 62-66. |
| [5] | 刘泽华, 卢洪涛, 李伟, 等. 基于R语言的ARIMA模型在医用耗材消耗量短期预测中的应用研究[J]. 医疗卫生装备, 2024, 45(10): 84-87. |
| [6] | 詹平, 刘飞翔, 赵嘉良. 基于LDA和ARIMA模型的煤矿安全隐患数量预测研究[J]. 煤, 2024, 33(3): 39-44. |
| [7] | 吴会会, 王嘉鹏, 吴文静, 等. 基于ARIMA模型的全球气表温度预测分析[J]. 现代信息科技, 2023, 7(16): 147-150. |
| [8] | Gao, W., Xiao, T., Zou, L., Li, H. and Gu, S. (2024) Analysis and Prediction of Atmospheric Environmental Quality Based on the Autoregressive Integrated Moving Average Model (ARIMA Model) in Hunan Province, China. Sustainability, 16, Article 8471. https://doi.org/10.3390/su16198471 |
