A hybrid knowledge and model system for R&D project selection

被引：42
|
作者：
Tian, QJ
Ma, J
Liu, O
机构：
[1] City Univ Hong Kong, Dept Informat Syst, Kowloon, Hong Kong, Peoples R China
[2] Shandong Univ Sci & Technol, Dept Comp Sci, Shandong, Peoples R China
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2002年 / 23卷 / 03期
关键词：
decision support systems; knowledge-based systems; model management; R&D project selection;
D O I：
10.1016/S0957-4174(02)00046-5
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Decision models and knowledge rules are widely used to assist in decision-making. They are common decision support devices that should be effectively managed in decision support systems. Research and development (R&D) project selection is a complicated and knowledge intensive decision-making process where decision models and knowledge rules play an important role. This paper presents a hybrid knowledge and model system, which integrates mathematical models with knowledge rules, for R&D project selection. The system is designed to support the whole decision process of R&D project selection and has been used in the selection of R&D projects in the National Natural Science Foundation of China (NSFC). (C) 2002 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：265 / 271
页数：7
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