Dynamic Evaluation and System Coordination Study of Asset Valuation Based on Deep Learning. (28th June 2022)
- Record Type:
- Journal Article
- Title:
- Dynamic Evaluation and System Coordination Study of Asset Valuation Based on Deep Learning. (28th June 2022)
- Main Title:
- Dynamic Evaluation and System Coordination Study of Asset Valuation Based on Deep Learning
- Authors:
- Liu, Lige
Chen, Shenge - Other Names:
- Cao Ning Academic Editor.
- Abstract:
- Abstract : With the rapid development of artificial intelligence, the information construction of the database plays a very important role in various industries, such as the field of asset appraisal. Therefore, we can use deep learning technology to carry out a dynamic evaluation of asset appraisal, simultaneously adjust, and improve the coordination degree for such system. In this paper, according to asset appraisal theory, we conduct a comprehensive scientific study on asset appraisal about the information construction of the database and the evaluation system, which is conducive to promote the self-improvement and development of the asset appraisal industry in terms of internal control construction. Experimental results show that our method using DL (deep learning) can well accomplish the dynamic evaluation of asset appraisal with competitive performance.
- Is Part Of:
- Mathematical problems in engineering. Volume 2022(2022)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06-28
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2022/1056869 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 22316.xml