Regional Manufacturing Industry Demand Forecasting: A Deep Learning Approach

被引:19
|
作者
Dou, Zixin [1 ]
Sun, Yanming [1 ,2 ]
Zhang, Yuan [1 ,3 ]
Wang, Tao [4 ]
Wu, Chuliang [5 ]
Fan, Shiqi [6 ]
机构
[1] Guangzhou Univ, Sch Management, Guangzhou 510000, Peoples R China
[2] Guangzhou Univ, Res Ctr High Qual Dev Modern Ind, Guangzhou 510000, Peoples R China
[3] Guizhou Univ Commerce, Sch Management, Guiyang 550014, Peoples R China
[4] Univ Malaya, Fac Built Environm, Dept Bldg Surveying, Kuala Lumpur 50603, Malaysia
[5] Guangzhou Univ, Sch Math & Informat Sci, Guangzhou 510000, Peoples R China
[6] Univ Hong Kong, Dept Engn, Hong Kong 999077, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 13期
关键词
manufacturing industry; demand forecasting; influence factor; deep learning; ECONOMIC-GROWTH; SERVICES; PERFORMANCE; INVESTMENT; PREDICTION; INNOVATION;
D O I
10.3390/app11136199
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
With the rapid development of the manufacturing industry, demand forecasting has been important. In view of this, considering the influence of environmental complexity and diversity, this study aims to find a more accurate method to forecast manufacturing industry demand. On this basis, this paper utilizes a deep learning model for training and makes a comparative study through other models. The results show that: (1) the performance of deep learning is better than other methods; by comparing the results, the reliability of this study is verified. (2) Although the prediction based on the historical data of manufacturing demand alone is successful, the accuracy of the prediction results is significantly lower than when taking into account multiple factors. According to these results, we put forward the development strategy of the manufacturing industry in Guangdong. This will help promote the sustainable development of the manufacturing industry.
引用
收藏
页数:15
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