Regional manufacturing industry demand forecasting: A deep learning approach
Document Type
Article
Publication Date
7-1-2021
Abstract
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.
Keywords
Manufacturing industry, Demand forecasting, Influence factor, Deep learning
Divisions
BuiltEnvironment
Funders
National Natural Science Foundation of China (NSFC) [71571072],National Social Science Foundation [18BGL236],Guangdong Province Key Research and Development Project [2020B0101050001],Special Fund for Science and Technology Innovation Strategy of Guangdong Province [pdjh2021b0405]
Publication Title
Applied Sciences
Volume
11
Issue
13
Publisher
MDPI
Publisher Location
ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND