A hybrid knowledge and model system for R&D project selection
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 265-271 |
| Journal / Publication | Expert Systems with Applications |
| Volume | 23 |
| Issue number | 3 |
| Publication status | Published - 1 Oct 2002 |
Link(s)
Abstract
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). © 2002 Elsevier Science Ltd. All rights reserved.
Research Area(s)
- Decision support systems, Knowledge-based systems, Model management, R&D project selection
Citation Format(s)
A hybrid knowledge and model system for R&D project selection. / Tian, Qijia; Ma, Jian; Liu, Ou.
In: Expert Systems with Applications, Vol. 23, No. 3, 01.10.2002, p. 265-271.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
