Yuan Yana
School of Economics and Management, Hainan Normal University, Haikou 571158, China.
Appl Bionics Biomech. 2022 Oct 11;2022:2206689. doi: 10.1155/2022/2206689. eCollection 2022.
Entering the era of knowledge economy, the economic value of talent education is more and more emphasized, and it contributes more and more to the local economy and injects new vitality into local economic development. However, there are still some difficulties in the synergistic development of talent education and local economy, such as the low degree of integration of "industry, profession, and employment" and the lack of synergy between schools and enterprises, which affects the high-quality development of talent education and restricts the long-term development of regional economy. This paper incorporates machine learning algorithms to construct a multivariate statistics analysis model based on the correlation analysis model between talent training quality and regional economic development. Based on the multi-variate statistical analysis theory and method, the qualitative analysis and quantitative analysis are closely combined to scientifically pick up the main indicators affecting the comprehensive quality of talent cultivation and overcome the drawbacks of artificial subjective assignment of values. Through the judicious selection of evaluation indexes, a scientific and fair evaluation model is established, and the targets of talent cultivation are combined with regional economic development, in a comprehensive analysis, which provides a new means for the development of the regional economy.
进入知识经济时代，人才教育的经济价值越来越受到重视，它对地方经济的贡献越来越大，为地方经济发展注入了新的活力。然而，人才教育与地方经济协同发展仍存在一些困难，如“产业、专业、就业”一体化程度低，学校与企业缺乏协同，影响人才教育高质量发展，制约区域经济长远发展。本文引入机器学习算法，基于人才培养质量与区域经济发展的关联分析模型构建多元统计分析模型。基于多元统计分析理论和方法，将定性分析与定量分析紧密结合，科学选取影响人才培养综合素质的主要指标，克服人工主观赋值的弊端。通过合理选择评价指标，建立科学公正的评价模型，将人才培养目标与区域经济发展相结合进行综合分析，为区域经济发展提供了新手段。
