Abstract
Research and development (R&D) talents training are asymmetric in China universities and can be of great significance for economic and social sustainable development. For the purpose of making an in-depth analysis in the education management costs for R&D talents training, the belief rule-based (BRB) expert system with data increment and parameter learning is developed to achieve education management cost prediction for the first time. In empirical analysis, based on the BRB expert system, the past investments and future planning of education management costs are analyzed using real education management data from 2001 to 2019 in 31 Chinese provinces. Results show that: (1) the existing education management cost investments have a significant regional difference; (2) the BRB expert system has excellent accuracy over some existing cost-prediction models; and (3) without changing the current education management policy and education cost input scheme, the regional differences in China’s education management cost input always exist. In addition to the results, the present study is helpful for providing model supports and policy references for decision makers in making well-grounded plans of R&D talents training at universities
Highlights
Due to the education management data related with 31 provinces, a total of 31 belief rule-based (BRB) expert systems needs to be constructed for each year while investigating education management cost planning
This study focused on the discussion of research and development (R&D) talents training in China universities based on education management cost planning
The R&D talents training in China universities was studied based on the consideration of education management cost planning
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. In order to effectively analyze the relationship between R&D talents training and education funding [6], an effective cost-prediction model must be selected for education management cost planning. Owing to the BRB expert system and its improvements, the education management cost-prediction model is capable of providing a reference for the policy making of education management in universities and provides an effective prediction tool for the policy implementers and long-term planners of the education management cost to promote the sustainable development of R&D talents training in China. The remainder of this research is structured as follows: Section 2 presents the preliminaries of the study This is followed by a new education management cost-prediction model.
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