Assessment and Prediction of Enterprise's Innovation Capability Based on Variational AutoEncoder and Long Short-Term Memory Network
Under the background of innovation capability as the key driving force of enterprise development, this paper proposes an enterprise innovation capability assessment and prediction method based on Variational AutoEncoder (VAE) and Long Short-Term Memory Network (LSTM). And the effectiveness of the proposed method is verified by the data of 133 listed companies, and the proposed method can realize the quantitative assessment and prediction of enterprise innovation capability.
Authors
- Zhisen Chen
- Xiaochen Zhang (ORCID: https://orcid.org/0000-0002-3157-7748)
- Tang Lingling (ORCID: https://orcid.org/0000-0003-3105-3765)
Institutions
- Fujian Normal University (CN)
- Guangdong University of Foreign Studies (CN)
Publication Details
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1145/3714334.3714347
- Primary Topic
- Innovation Policy and R&D
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Guangdong University of Foreign Studies