Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry

Bowen Cai and Naeem Jan

Journal of Mathematics, 2021, vol. 2021, 1-10

Abstract: Recently the issues of insufficient energy and serious air pollution around the world have been rising. Henceforth, there is a need to carry out a research of new energy. Soon, new energy vehicles will be the mainstream trend, which can not only reduce the burden of consumers due to rising fuel prices but also solve the air pollution problem caused by the exhaust emissions of fuel vehicles. With the rapid development of science and technology, deep learning continues to make breakthroughs, and, in the field of economy with huge information data, we have more powerful weapons available to predict and research important economic data with infinite value, which can not only provide reference information to policy makers but also help enterprises and even economic markets to develop more healthily and sustainably. Therefore, this article uses deep learning algorithms to forecast and analyze the new energy industry, starting from the financial information released by new energy vehicle companies in their annual reports, in order to make basic judgments and help policy makers and enterprises in the new energy vehicle industry.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:3870657

DOI: 10.1155/2021/3870657

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