Evaluation and Verification of Patent Value Based on Combination Forecasting Model
This paper studies a combination forecasting model with strong adaptability and high dimension to evaluate value of patents, and verifies the model empirically in the research. Through the AHP analysis, five necessary factors that affect the value of patents are discovered, which come from both the...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2022.2.0058 |
| _version_ | 1797688790864625664 |
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| author | Xiao Xiaoqing Duan Xinhui Zhao Yongfa Pan Junzhen Shen Guiquan Pan Xiaomei Wang Quanxi Lutfi Bishr |
| author_facet | Xiao Xiaoqing Duan Xinhui Zhao Yongfa Pan Junzhen Shen Guiquan Pan Xiaomei Wang Quanxi Lutfi Bishr |
| author_sort | Xiao Xiaoqing |
| collection | DOAJ |
| description | This paper studies a combination forecasting model with strong adaptability and high dimension to evaluate value of patents, and verifies the model empirically in the research. Through the AHP analysis, five necessary factors that affect the value of patents are discovered, which come from both the characteristic factors of the patent itself and the institutional characteristic factors that attempt to transform the patent. We’ve constructed a state space model through some data that can already obtain the added value of its patent through the Hejun value evaluation model and deployed the state space model in the artificial intelligence data space to have the neural network training. Another part of the known data is used to empirically verify this model, and it is found that the data fits well. Not only can the model be used for patent conversion institutions to evaluate patents, but also for patent holders to evaluate patent conversion institutions. |
| first_indexed | 2024-03-12T01:35:46Z |
| format | Article |
| id | doaj.art-08765182c75944d78e95a679febb3975 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-12T01:35:46Z |
| publishDate | 2023-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-08765182c75944d78e95a679febb39752023-09-11T07:01:08ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562023-01-018171572210.2478/amns.2022.2.0058Evaluation and Verification of Patent Value Based on Combination Forecasting ModelXiao Xiaoqing0Duan Xinhui1Zhao Yongfa2Pan Junzhen3Shen Guiquan4Pan Xiaomei5Wang Quanxi6Lutfi Bishr71Guangdong Power Grid Corporation, Guangzhou, 510000, China1Guangdong Power Grid Corporation, Guangzhou, 510000, China1Guangdong Power Grid Corporation, Guangzhou, 510000, China1Guangdong Power Grid Corporation, Guangzhou, 510000, China1Guangdong Power Grid Corporation, Guangzhou, 510000, China1Guangdong Power Grid Corporation, Guangzhou, 510000, China1Guangdong Power Grid Corporation, Guangzhou, 510000, China2College of Administrative Sciences, Applied Science University, BahrainThis paper studies a combination forecasting model with strong adaptability and high dimension to evaluate value of patents, and verifies the model empirically in the research. Through the AHP analysis, five necessary factors that affect the value of patents are discovered, which come from both the characteristic factors of the patent itself and the institutional characteristic factors that attempt to transform the patent. We’ve constructed a state space model through some data that can already obtain the added value of its patent through the Hejun value evaluation model and deployed the state space model in the artificial intelligence data space to have the neural network training. Another part of the known data is used to empirically verify this model, and it is found that the data fits well. Not only can the model be used for patent conversion institutions to evaluate patents, but also for patent holders to evaluate patent conversion institutions.https://doi.org/10.2478/amns.2022.2.0058combination forecasting modelpatent value evaluationpatent added valueartificial intelligencestate space model34a34 |
| spellingShingle | Xiao Xiaoqing Duan Xinhui Zhao Yongfa Pan Junzhen Shen Guiquan Pan Xiaomei Wang Quanxi Lutfi Bishr Evaluation and Verification of Patent Value Based on Combination Forecasting Model Applied Mathematics and Nonlinear Sciences combination forecasting model patent value evaluation patent added value artificial intelligence state space model 34a34 |
| title | Evaluation and Verification of Patent Value Based on Combination Forecasting Model |
| title_full | Evaluation and Verification of Patent Value Based on Combination Forecasting Model |
| title_fullStr | Evaluation and Verification of Patent Value Based on Combination Forecasting Model |
| title_full_unstemmed | Evaluation and Verification of Patent Value Based on Combination Forecasting Model |
| title_short | Evaluation and Verification of Patent Value Based on Combination Forecasting Model |
| title_sort | evaluation and verification of patent value based on combination forecasting model |
| topic | combination forecasting model patent value evaluation patent added value artificial intelligence state space model 34a34 |
| url | https://doi.org/10.2478/amns.2022.2.0058 |
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