情报科学 ›› 2021, Vol. 39 ›› Issue (1): 157-162.

• 博士论坛 • 上一篇    下一篇

基于熵值法的我国省际生态数据评价研究 

  

  • 出版日期:2021-01-01 发布日期:2021-01-25

  • Online:2021-01-01 Published:2021-01-25

摘要: 【目的/意义】构建科学的生态数据评价模型是生态文明建设的重要内容,需要从针对性、严谨性入手对数
据进行归纳分析,为提高评价体系的准确性提供有力数据支撑。【方法
/过程】本文以我国省际生态指数为例,运用
熵值法对评价指标、权重进行优化,通过数据模型的构建,从海量数据中筛选出能够科学、精准地评价我国省际当
前生态文明建设现状的数据指标。【结果
/结论】基于熵值法的评价模型,合理地解决了评价体系评价不精准、不符合
实际的问题
,展示了省际生态发展情况,提出了我国省际生态发展评价问题的解决途径,实证研究的结果表明该评
价方法是科学的。【创新
/局限】本文利用改进的熵值法,得到我国省际生态指数数据评价模型,用于后续的综合评
价。鉴于数据的可获得性,部分研究采取了数值模拟方法,未来要完善计量模型分析,进一步提高结果的精准度。

Abstract: Purpose/significanceConstructing scientific ecological data evaluation model is an important content of ecological civili⁃
zation construction. It is necessary to start with pertinence and rigor to summarize and analyze the data to provide strong data support
for improving the accuracy of the evaluation system.
Method/processTaking China's inter-provincial ecological index as an exam⁃
ple, this paper uses entropy method to optimize the evaluation index. Through data model construction and weight measurement, the
data indexes that can scientifically and accurately evaluate China's current ecological civilization construction status can be screened
out from the massive data.
Result/conclusionThe evaluation model based on entropy value method reasonably solves the problem of
inaccurate evaluation system evaluation and does not accord with the reality, shows the situation of inter-provincial ecological develop⁃
ment, and puts forward the solution to the evaluation problem of inter-provincial ecological development in China. The empirical re⁃
search results show that the evaluation method is scientific.
Innovation/limitationThis paper uses the improved entropy method to
obtain the data evaluation model of China's inter-provincial ecological index, which can be used for subsequent comprehensive evalua⁃
tion. In view of the availability of data, some studies adopted numerical simulation methods to improve the econometric model analysis
in the future and further improve the precision of the results.