摘要
提出了一种改进粗糙集的R&D项目的中止决策方法,该方法应用向量空间理论知识在一定程度上改进了粗糙集中属性约简以及规则提取的算法,解决了R&D项目中止决策中产生的样本较小时粗糙集属性约简计算量大和特征提取规律不明显的问题,同时根据以往同类R&D项目失败或成功的经验作为学习样本,识别R&D项目的类别,从而做出中止还是继续进行的决策。最后以重庆市某大型企业近几年的R&D项目进展情况为实例,使用该方法和支持向量机两种方法进行了计算,对该方法进行了可行性和有效性验证。
a kind of decision algorithm of R＆D project termination based on improved rough set theory is proposed. The algorithm makes use of the vector space theory to improve the attributes reduction and the rules extraction in the rough set theory and to resolve the questions that calculation of reduction is huge and characteristic is not clear when there are few samples of R＆D project to some extent. At the same time,considering R＆D project experience that is aborted or successful in the past as samples for learning, it can discern the classification of R＆D project with uncertain feature so as to make decision of termination or continued studying. Finally, the feasibility and validity of this algorithm are testified by the instance from a large - scaled enterprise in Chongqing and the comparison with the results by using supported vector machine.
出处
《中国管理科学》
CSSCI
2005年第6期86-90,共5页
Chinese Journal of Management Science
基金
重庆市科学技术计划资助项目(7117)
关键词
R&D项目
中止决策
粗糙集
向量空间
支持向量机
R＆D project
termination decision
rough set theory
vector space
support vector machine
