计算机工程与应用 ›› 2016, Vol. 52 ›› Issue (23): 102-108.

• 大数据与云计算 • 上一篇    下一篇

改进财务评价指标体系的筛选研究

张文宇1,陶  蓉1,陈  星2,任  露1   

  1. 1.西安邮电大学 经济与管理学院,西安 710061
    2.石家庄邮电职业技术学院 会计系,石家庄 050000
  • 出版日期:2016-12-01 发布日期:2016-12-20

Screening study of improved financial evaluation indexes system

ZHANG Wenyu1, TAO Rong1, CHEN Xing2, REN Lu1   

  1. 1.College?of?Economic?and?Management, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
    2.Department of Accounting, Shijiazhuang Posts and Telecommunications Technical College, Shijiazhuang 050000, China
  • Online:2016-12-01 Published:2016-12-20

摘要: 为解决目前传统项目财务评价指标存在的意义重复、通用性欠佳等不足,提出了指标改进与技术筛选相结合的体系模型。首先根据传统指标的不足,提出新的改进财务评价指标,形成更加完善的指标体系;进而运用因子分析与聚类分析相结合的数据挖掘方法对改进的投资项目财务评价指标体系进行筛选,提高了财务评价的准确性及计算效率;最后应用实例验证了数据挖掘技术在投资项目财务评价指标研究中的有效性,为项目财务评价工作者提供一种改进的思路与方法。

关键词: 投资项目, 财务评价指标, 因子分析, 聚类分析

Abstract: In order to solve the traditional project financial evaluation of the significance of the presence of duplication and poor lack of versatility, the system model is proposed which combines indicators improvement and screening technology. Firstly, according to the deficiencies of traditional indicators, it proposes new improved financial evaluation, to form a more perfect indicator system. Then it uses data mining methods of factor analysis and cluster analysis of the combination of an improved project financial evaluation index system for screening, improves financial accuracy and computational efficiency evaluation. Finally, application examples demonstrate the effectiveness of data mining techniques in evaluation research project finance for the project financial evaluation workers to provide an improved idea and method.

Key words: investment projects, financial evaluation index, factor analysis, cluster analysis