Full
Outline
Given that traditional patent value evaluation methods are easily influenced by subjective factors and struggle to comprehensively and objectively reflect the value of patents, this study proposed a patent value evaluation method to identify high-value patents.
This study employs information gain and variance analysis methods to perform feature selection on patent data from medical universities, optimizing input features and reducing redundant information. In terms of model construction, a three-layer BP neural network structure was designed, incorporating ReLU activation functions and Dropout techniques to mitigate overfitting issues and enhance the model's ability to handle nonlinear relationships, thereby improving the model's stability and generalization.
The experimental results showed that the model achieved a prediction accuracy of 96%. Feature selection effectively improved the model's performance to a certain extent, demonstrating good results across multiple evaluation metrics and verifying the feasibility of the proposed method.
This study provides a feasible and effective practical method for patent value evaluation in medical universities, offering valuable reference and application significance, particularly in the identification and prediction of high-value patents.
52
7
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
