CAJ | 학술논문

从区域发展指标体系下数据所蕴含信息量的角度出发，建立以信息熵为衡量标准的评价方式，研究如何利用模糊C均值聚类分类改进数据信息量，并从理论证明和实证分析的角度验证了方法的有效性。采用皖北沿淮地区在综合指标体系下的面板数据进行改进实验，结果表明在熵的标准下数据呈现多样性，信息量得到了显著提高，为后续采用数据挖掘方法进行指标讨论奠定了更好的数据信息质量。
종구역발전지표체계하수거소온함신식량적각도출발，건립이신식적위형량표준적평개방식，연구여하이용모호C균치취류분류개진수거신식량，병종이론증명화실증분석적각도험증료방법적유효성。채용환북연회지구재종합지표체계하적면판수거진행개진실험，결과표명재적적표준하수거정현다양성，신식량득도료현저제고，위후속채용수거알굴방법진행지표토론전정료경호적수거신식질량。
Based on information entropy from the perspective of data quantity under index system of regional de-velopment, this paper establishes the way of evaluation by the standard of information entropy, explores how to improve the information of data using fuzzy c-means algorithm, and validates the the proposed method from the-oretical proof and empirical analysis.The paper makes improving experiments via panel data under comprehensive index system of regions of northern Anhui and along the Huaihe river.Its result suggests diversity in data by infor-mation entropy standard and marked improvement of information, which lays good basis of better data quality for consequent data mining.