Work

Regional Manufacturing Industry Demand Forecasting: A Deep Learning Approach

Year: 2021

Type: article

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.

Source: Applied Sciences

DOI: 10.3390/app11136199

Authors: Zixin Dou, Yanming Sun, Yuan Zhang, Tao Wang, Chuliang Wu, Shiqi Fan

Institutions: Guangzhou University, Guizhou University of Commerce, University of Malaya, University of Hong Kong

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,160