科研管理 ›› 2013, Vol. ›› Issue (6): 122-128.

• 论文 • 上一篇    下一篇

多维框架证据推理的科研项目立项评估方法

张洪涛1,2, 朱卫东2, 王慧1, 吴勇2   

  1. 1. 安徽理工大学理学院, 安徽 淮南 232001;
    2. 合肥工业大学管理学院, 安徽 合肥 230009
  • 收稿日期:2011-08-22 修回日期:2012-05-15 出版日期:2013-06-27 发布日期:2013-06-18
  • 基金资助:
    国家自然科学基金:两维语义的证据推理理论与系统研究(71071048,2011.1~2013.12);高等学校省级优秀青年人才基金重点项目:多维框架证据推理方法及其在多属性群决策中的应用(2012SQRW031ZD,2012.1~2014.12)。

An evaluation method for scientific research project selectionbased on the evidential reasoning algorithm under multi-dimensional frames of discernment

Zhang Hongtao1,2, Zhu Weidong2, Wang Hui1, Wu Yong2   

  1. 1. School of Science, Anhui University of Science and Technology, Huainan 232001, China;
    2. School of Management, Hefei University of Technology, Hefei 230009, China
  • Received:2011-08-22 Revised:2012-05-15 Online:2013-06-27 Published:2013-06-18

摘要: 针对现行科研项目立项评估方法中存在的不足,提出多维框架证据推理的科研项目立项评估方法。根据多个识别框架之间的逻辑关系,给出平行框架、递进框架和混合框架的概念;将同行评议表中的"熟悉程度"和"综合评价等级"、"熟悉程度"和"资助意见"视为两个平行的递进框架,分别将两个递进框架评价信息转化为证据体,用评价等级(资助意见)和信度表示专家的评审意见,从而即能方便描述专家评价中的不完全信息,又能充分整合评审中有价值的信息;利用"熟悉程度"对专家进行赋权,利用证据推理算子将专家评估信息分别在两个平行框架上集结,并将不同项目进行量化排序择优;最后结合实例来检验该方法的有效性。

关键词: 科研项目, 立项评估, 多维框架, 证据推理

Abstract: To overcome the disadvantages of existing evaluation methods for scientific research project selection, a new evaluation approach based on the evidential reasoning algorithm under multi-dimensional frames of discernment is proposed. According to the logical relationship, the frames of discernment are distinguished to the parallel frame, progressive frame, and mixed frame. The comprehensive evaluation grade with the degree of familiarity and the funding advice plus the degree of familiarity in the peer review form are regarded as two parallel progressive frames and are transformed into pieces of evidence, where the peer reviews could be expressed by evaluation grades (funding advice) with belief. In this way, the incomplete information of peer reviews is able to be easily described and the valuable information of assessment could be fully integrated. Then the expert weights are given by the degree of familiarity and the peer reviews are integrated on two parallel frames, respectively by using the evidential reasoning operator. And then the evaluations of scientific research projects are quantified and selected. Finally, an example is given to check the validation of the approach.

Key words: scientific research project, project selection, multi-dimensional frame, evidential reasoning

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