Research On The Driven Factors Of Patents Application

Patent is the most core and valuable part of a regional science and technology assets. The possession quantity of patents, which is the most important mark to describe the regional innovation ability and comprehensive strength, not only reflects the original innovation ability of this region, but also reflects the application ability of these achievements. It has been widely concerned that how to do the research in the framework of regional innovation. But the research of driven factors of patents application has not been paid enough attention. So it is very important both for theory and practice that the drivers are chosen as the study object.Under the background that national patents strategy vigorously promotes, intellectual property strategy improved, and the regional innovation strengthened, patent applications drive system is deeply studied using a combination of qualitative and quantitative methods. During this study, one side through support vector machine (SVM) model for the patent applications drivers, P-SVM is used to select the non-linear key driver, and negative binomial distribution model is used to evaluate the key drivers. Another side, the assumption of drivers of China's patent applications is presented and the existence is analyzed by the relationship research and confirmatory factor analysis. The main content and innovative research results are as follows:(1) This article refers to the patent applications related to the driver of the theory, from the international comparative study of international research development, economic growth, corporate strategy and the degree of patent protection, a research perspective and the starting point are presented in this article, and the patent applications drivers are analyzed. In this article, the regional technological innovation is the core and the activities of patent applications are the link, and it is analyzed of China's regional innovation system's patented technology features. Driven system of patent applications is presented based on regional technological innovation. On the basis of the patent applications in the driver's selection principles, the development of patents, patent development, business investment and government investment, research and contact with foreign investment drive, and other factors are analyzed.(2) In this work, on the basis of machine learning and statistics, support vector machine regression model is introduced for patent applications. Regional investment funds, manpower, patents tend to regional prosperity and foreign investment-driven activities are included in the modeling process as variable factors. The simulation methods of the patent application drivers to predict results show that support vector machines than the forecast of artificial neural networks and logistic regression methods have higher forecast accuracy, but also showed that the use of support vector machine approach to our patent application of the drivers Modeling is a feasible and effective in order to also deal with the non-linear regression prediction of a possible solution.(3) On the success of support vector machine modelling of the patent application, P-SVM is used in patent applications for selected key drivers. In the process of running P-SVM, for the P-SVM parameters, three parallel differential evolution algorithm for the selection of successful patent applications to select a key driver of variables, such as: the total regional GDP, per million people in college The number of qualifications, the total number of pre-owned patents, second and third production ratio of the number of practitioners, R&D staff, corporate R&D funds accounted for sales ratio, the total regional R&D expenditure proportion of GDP accounted for, universities and research institutes access to corporate R&D funding And the per capita foreign direct investment, and so on. Papers selected after the use of variable factors on China's further regional patent applications to predict, data simulation shows a good feature extraction function of the P-SVM than kernel PCA least squares and support vector machine regression ridge of high forecast Precision and the ability to promote. The pilot study showed that P-SVM modelling approach in dealing with this kind of patent applications drive drivers return to the issue of non-linear feature selection to be effective.(4) Based on the patent applications in the evaluation of the Poisson distribution model, and considering our patent application of the characteristics of the sample data, a patent application for evaluation of the negative binomial distribution model adopted by the negative binomial distribution model for the evaluation of the use of panel data Eastern, central and western areas of patent applications drivers were evaluated, analyzed and discussed. The results show that: the regional GDP, the total number of pre-patent owners, corporate R&D funds accounted for sales ratio, R&D expenditures of the total proportion of GDP accounted for, the four factors of east, middle and west of China variable in the three regions of the patent application has a strong drive Role; the total number of pre-owned patents, corporate R&D funds accounted for sales ratio, R&D expenditure accounted for the total proportion of GDP. These three factors also east, middle and west of China variable in the three regions of the invention patent applications has a strong drive, other Factor in the different regions for different degree of innovation and performance varied.(5) The patent application for the quantitative study of the drivers added that empirical method is used for China's patent application drivers. In this paper, the assumptions related to the patent applications and drivers are referred using of regional research data, patent applications and drivers of the relationship between the confirmatory factor analysis and the results indicated that the eastern region to support the assumption that the system, the central and western regions. To support the assumption that part of the system. The article for the central and western regions of the empirical conclusions were discussed, and the development of the patent awareness, legal environment, market, technology, independent intellectual property rights and patent life-cycle process, and other aspects of the central and western regions of the patent development, improve the regional innovation strategies suggestion.The research work in the dissertation have partly solved the problems of non-linear model for the patent applications drivers, feature extraction and evaluation, provided a broader space for the non-linear regression prediction, similer to the driven factors of patents application.