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A hybrid system applied to epidemic screening
Author(s) -
Xu Li Da,
Li Ling X
Publication year - 2000
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/1468-0394.00130
Subject(s) - computer science , case based reasoning , expert system , artificial intelligence , model based reasoning , reasoning system , focus (optics) , rule based system , qualitative reasoning , machine learning , encoding (memory) , data mining , knowledge representation and reasoning , physics , optics
Although many knowledge‐based systems (KBSs) focus on single‐paradigm approaches to encoding knowledge (such as production rules), human experts rarely use a single type of knowledge to solve a real‐world problem. A human expert usually combines a number of reasoning mechanisms. In recent years, rule‐based reasoning (RBR), case‐based reasoning (CBR) and model‐based reasoning (MBR) have emerged as important and complementary reasoning methodologies in the intelligent systems area. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid epidemic screening KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed. The system has been tested using real epidemic screening variables and data.