Research On The Level Analysis Of Regional Innovation Ability

The concept of "public entrepreneurship and innovation" has gradually penetrated into the hearts of the people.Building an innovative country has become China’s development goal.Innovation has become a key driving force for industrial upgrading From the national level to the provincial territory to the city,it is actively improving its independent innovation capacity;To build a strong innovation country,we must rely on regional innovation and the main body of innovation.China is currently in a critical period of industrial upgrading and structural adjustment.Innovation is the first driving force and a key factor for success.In this context,this article studies regional innovation,from provincial administrative districts to urban agglomerations,and then to the top 100 cities,from a statistical perspective to analyze the level of regional innovation capability in China.First of all,a descriptive statistical analysis of China’s regional innovation was carried out,and a conclusion was drawn that China’s regional innovation difference is obvious;regression analysis establishes multiple regression equations,and analyzes that the number of R&D personnel is the most significant influencing variable of patents;K-Means clustering analysis method was used to comprehensively rank the innovation level of 31 provincial administrative regions.Secondly,two methods of objective and subjective weight factor analysis and analytic hierarchy were used to evaluate and rank the innovation capacity of provincial administrative regions.The highest score was Beijing,and the ranking of eastern provinces was significantly higher than that of central and western regions.The ranking results of the two methods are compared.Once again,it analyzes the innovation competitiveness of the top 100 economic cities.It is divided into three levels of indicators.The first level is the innovation competitiveness,that is,the comprehensive score of innovation.The second level includes five aspects,namely the innovation base and the innovation environment.,Innovation input and innovation sustainable development ability,two methods of objective weighting entropy weight method and BP neural network are used under the same indicators and samples.This paper analyzes the differences in urban innovation levels from the perspectives of secondary index ranking,comprehensive score ranking,and comparison line ranking,and discusses the matching degree of urban economic strength and innovation ability,which has an important reference role for urban industrial development.By comparing the evaluation results of the two methods,the differences of the algorithms are analyzed.Finally,according to the results of the previous part of the analysis,some suggestions are put forward,as well as research conclusions and prospects.The main innovations of this article are:(1)Multi-dimensional and multi-level analysis of regional innovation levels;(2)Empirical analysis of provincial innovation differences using subjective and objective weighting comparison methods;(3)Entropy weight Method,BP neural network two methods for regional innovation empirical analysis of the same indicators,the same sample,and BP neural network as one of the methods of machine learning,has the advantage of predictive function,and plays an important role in building an innovation evaluation system.