Development of Patent Technology Prediction Model Based on Machine Learning

Abstract

Intellectual property rights have a great impact on the development of the automobile industry. Issues related to the timeliness of patent applications often arise, such as the inability of firms to predict new technologies and patents developed by peers. To find the proper direction of product development, the R&D departments of enterprises need to accurately predict the technology trends. Machine learning adopts calculation through a large amount of data through mathematical models and methods and finds the best solution at the fastest speed through repeated simulation and experiments, to provide decision makers with a reference basis. Therefore, this paper provides accurate forecasts through established models. In terms of the significance of management, the planning of future enterprise strategy can be divided into three stages as a short-term plan of 1–3 years, a medium-term plan of 3–5 years, and a long-term plan of 5–10 years. This study will give appropriate suggestions for the development of automobile industry technology.

Keywords

• patent technology
• intellectual property
• automobile industry
• artificial neural network
• machine learning
• ensemble learning