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Research on the construction and application of an invention patent model based on TFAHP-FAHP algorithm.

Authors :
Wang, Chong
Source :
Journal of Computational Methods in Sciences & Engineering. 2024, Vol. 24 Issue 3, p1423-1439. 17p.
Publication Year :
2024

Abstract

The TFAHP-FAHP algorithm model constructed in this article can preferably avoid subjective assumptions caused by human factor. The new energy vehicle power battery is a core component for improving the performance of electric vehicles, and constitutes one of the most valuable parts of the invention patent for new energy vehicles. Patent pledge financing is a brand new form with great potential. However, as a result of the imperfect system of the patent pledge financing, banks and other financial institutions are exposed to an increased risk in the process of the patent pledge financing, which seriously limits the development of the patent pledge financing for power battery. In view of the above issues, this paper uses the SPSS reliability and validity tests in order to develop a relatively complete and accurate index system. TFAHP algorithm model and fuzzy comprehensive are combined to determine the final correction coefficient. In this study, the income method is used to determine the pledge valuation value of a new energy vehicle power battery patent portfolio, and the AHP algorithm method is used to determine the weight of the value of the invention patent portfolio within the patent portfolio. As a result, in this paper, the pledge value of the patent portfolio is multiplied by a proportion of the invention patent portfolio's value, and then multiplied by a correction coefficient to obtain the final new energy vehicle power battery invention patent portfolio pledge value. Using this reference value, technology-based energy companies can pledge financing for new energy vehicle power battery invention patent portfolios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14727978
Volume :
24
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Computational Methods in Sciences & Engineering
Publication Type :
Academic Journal
Accession number :
178050845
Full Text :
https://doi.org/10.3233/JCM-247154