Dynamic evaluation of new energy vehicle policy based on text mining of PMC knowledge framework

Abstract

[Objective/Significance]The problems of policy structure and policy contents needs to be solved dynamically in the development process of new energy vehicle industry. Considering the limitation of traditional policy evaluation methods and the lack of knowledge support of policy text data mining, an optimized dynamic evaluation of new energy vehicle policy is deeply explored based on big data method of policy informatics and policy knowledge framework of PMC. The dynamic evolution process of new energy vehicle policy is deeply explored, policy deficiencies are analyzed, and optimization suggestions are proposed according to the realities of policy application scenarios. It has the theoretical significance of optimizing an evaluation method based on text data mining combined with policy knowledge, and perfecting the research in dynamic analysis, as well as the practical value of policy optimization for the high-quality development of new energy automobile industry. [Methodology/Process]Based on the PMC index model, two layers of dimensional framework is constructed for policy analysis, a new energy vehicle policy mining dictionary is established with the PMC knowledge framework by text mining and ontology semantic methods, to complete the machine assignment and dynamic evaluation of the PMC index model by text mining technology, the dynamic development process and existing problems of new energy vehicle policy is in-depth analyzed through the visualization results of PMC surface and concave index. [Results/conclusions]It is found that there are problems such as insufficient internal policy consistency, decreasing policy equilibrium, and expanding concave index of policy weaknesses. Finally, policy recommendations are proposed in terms of inter-governmental cooperation, policy multi-objective synergy, multi-functional policy optimization, policy instrument structure balance and policy details perfect.