A Fuzzy Description Logic Approach to Model Management in R&D Project Selection

Project selection is an important task in R&D project management. Several mathematical and decision models have been proposed for R&D project selection and current efforts have been on the effective model management approaches. In order to provide a formal and semantically rich method for model representation and to support content-rich formal reasoning, this paper proposes a fuzzy description logic approach to model management in R&D project selection. In the proposed approach, ontology engineering is applied to design the architecture of model management system, and fuzzy description logic is proposed to represent the modeling knowledge. Thus it can represent the imprecise and vague information, which is common in R&D project selection. A decision support system has also been developed based on the proposed approach. It is used to facilitate the selection of project proposals in the National Natural Science Foundation of China (NSFC). The application results show that the proposed method supports effective model management for R&D project selection.

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