Belief rule-base inference methodology using the evidential reasoning Approach-RIMER
| Autor: | H. S. Sii, Hongwei Wang, Jin Wang, Jian-Bo Yang, Jun Liu |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Knowledge representation and reasoning
business.industry Belief structure Evidential reasoning approach Inference Rule-based system Model-based reasoning Machine learning computer.software_genre Computer Science Applications Human-Computer Interaction Knowledge-based systems Control and Systems Engineering Case-based reasoning Artificial intelligence Electrical and Electronic Engineering business computer Software Mathematics |
| Zdroj: | IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 36:266-285 |
| ISSN: | 1083-4427 |
| DOI: | 10.1109/tsmca.2005.851270 |
| Popis: | In this paper, a generic rule-base inference methodology using the evidential reasoning (RIMER) approach is proposed. Existing knowledge-base structures are first examined, and knowledge representation schemes under uncertainty are then briefly analyzed. Based on this analysis, a new knowledge representation scheme in a rule base is proposed using a belief structure. In this scheme, a rule base is designed with belief degrees embedded in all possible consequents of a rule. Such a rule base is capable of capturing vagueness, incompleteness, and nonlinear causal relationships, while traditional if-then rules can be represented as a special case. Other knowledge representation parameters such as the weights of both attributes and rules are also investigated in the scheme. In an established rule base, an input to an antecedent attribute is transformed into a belief distribution. Subsequently, inference in such a rule base is implemented using the evidential reasoning (ER) approach. The scheme is further extended to inference in hierarchical rule bases. A numerical study is provided to illustrate the potential applications of the proposed methodology. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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