Diagnostic expert system using non-monotonic reasoning

doi:10.1016/S0957-4174(02)00032-5

2002-08-01

PRE

Ahmed Rafea

DOI：10.1016/S0957-4174(02)00032-5

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摘要

En 中文

The objective of this work is to develop an expert system for cucumber disorder diagnosis using non-monotonic reasoning to handle the situation when the system cannot reach a conclusion. One reason for this situation is when the information is incomplete. Another reason is when the domain knowledge itself is incomplete. Another reason is when the information is inconsistent. This method maintains the truth of the system in case of changing a piece of information. The proposed method uses two types of non-monotonic reasoning namely: 'default reasoning', and 'reasoning in the presence of inconsistent information' to achieve its goal. (C) 2002 Elsevier Science Ltd. All rights reserved.

Keyword:

expert systems

non-monotonic reasoning

cucumber disorder diagnosis