%0 Journal Article
%T 科技创新绩效影响因素分析及预测<br>Analysis and Prediction of Factors Affecting Science and Technology Innovation Performance
%A 张国强
%J Management Science and Engineering
%P 127-135
%@ 2167-6658
%D 2023
%I Hans Publishing
%R 10.12677/MSE.2023.122013
%X 结合数据分析和挖掘方法建立了一种理论模型，用于评价科技创新绩效。通过对科技创新绩效的众多相关的影响因素进行数据分析，采用Lasso回归方法识别科技创新绩效的关键影响因素，结合灰色预测方法、支持向量机预测模型，建立了科技创新绩效的评估预测模型。以历史数据为实证研究对象，拟合预测了科技创新绩效的期望值和未来发展趋势。<br />
A theoretical model was established for evaluating STI performance by combining data analysis and mining methods. Through data analysis of numerous relevant influencing factors of STI performance, Lasso regression method was used to identify the key influencing factors of STI performance, and combined with gray prediction method and support vector machine prediction model, a prediction model for evaluating STI performance was established. Using historical data as the empirical research object, the expected value and future development trend of science and technology innovation performance were fitted and predicted.
%K 科技创新绩效，数据分析与挖掘，支持向量机<br>Science and Technology Innovation Performance
%K Data Analysis and Mining
%K Support Vector 
Machines
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=62680