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Dominant Technology Identification of Wind Power Generation


Affiliations
1 School of Economics and Management, Harbin Engineering University, Harbin, China
2 Present address: No. 145, Nantong Street, Nangang District, Harbin City, Heilongjiang Province, China
 

Wind energy, the most commercialized prospect of renewable energy, is being developed and utilized on a large scale. Major institutions and universities have invested a lot of manpower, capital and technology in researching the wind power technology, which has made remarkable progress. In the era of green economy, the leading technology of wind power deserves more attention. Dominant technology represents the development direction of technology area. Identification of the dominant technology is of great significance for the technological choice and strategic layout of enterprises. In contrast to traditional technology identification methods, here we propose a visual analysis model based on patent citation relationship. First, the patent mutual citation data are input into the visualization software Gephi to identify the leading technology in the visual processing stage. The PageRank algorithm is used to cross contrast the technical value to build the leading technology recognition model. Second, we evaluate the technical value of each patent with five indices, including ‘number of patent cited’, ‘patent number of the same family’, ‘scope of patent coverage’, ‘claim number of each patent’, and ‘number of patent litigations’ to verify the accuracy of the visual model. Taking the database of wind power generation technology from European Patent Office as an example, we obtain 7421 patents from 1900 to 2017. The results of visual processing, evaluation of the index and PageRank judgment show that the visual model has a significant effect in the identification of the leading technology. The results also explain the applicability of the PageRank algorithm and the five indicators are the most scientific and reasonable for dominant technology identification.

Keywords

Leading Technology Identification, Patent Citation, Search Algorithms, Visual Analysis Model, Wind Power Generation.
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  • Dominant Technology Identification of Wind Power Generation

Abstract Views: 358  |  PDF Views: 121

Authors

Hongying Wang
School of Economics and Management, Harbin Engineering University, Harbin, China
Bing Sun
Present address: No. 145, Nantong Street, Nangang District, Harbin City, Heilongjiang Province, China

Abstract


Wind energy, the most commercialized prospect of renewable energy, is being developed and utilized on a large scale. Major institutions and universities have invested a lot of manpower, capital and technology in researching the wind power technology, which has made remarkable progress. In the era of green economy, the leading technology of wind power deserves more attention. Dominant technology represents the development direction of technology area. Identification of the dominant technology is of great significance for the technological choice and strategic layout of enterprises. In contrast to traditional technology identification methods, here we propose a visual analysis model based on patent citation relationship. First, the patent mutual citation data are input into the visualization software Gephi to identify the leading technology in the visual processing stage. The PageRank algorithm is used to cross contrast the technical value to build the leading technology recognition model. Second, we evaluate the technical value of each patent with five indices, including ‘number of patent cited’, ‘patent number of the same family’, ‘scope of patent coverage’, ‘claim number of each patent’, and ‘number of patent litigations’ to verify the accuracy of the visual model. Taking the database of wind power generation technology from European Patent Office as an example, we obtain 7421 patents from 1900 to 2017. The results of visual processing, evaluation of the index and PageRank judgment show that the visual model has a significant effect in the identification of the leading technology. The results also explain the applicability of the PageRank algorithm and the five indicators are the most scientific and reasonable for dominant technology identification.

Keywords


Leading Technology Identification, Patent Citation, Search Algorithms, Visual Analysis Model, Wind Power Generation.

References





DOI: https://doi.org/10.18520/cs%2Fv116%2Fi9%2F1525-1532