Abstract:
Case-base Reasoning (CBR) is an artificial
intelligent approach to learn and solve the problem emphasizes
the role of prior experience. Case-base reasoning methods have
to deal with the current problem to identify the situation , find a
past case similar to the next one, and use that case to suggest a
solution to the current problem, evaluate the proposed solution,
and update the system by learning from this paper is to develop
a case-based system where a new consequence event could be
quickly compared to the numerous cases in the databases. The
objective is to find the closest match that can be reused to
support the decision making for correct consequences event,
punishment and knowledge. In this paper, diagnosis system is
implemented for Traffic Enforcement Supervisory Committee of
Yangon Division System by using CBR. 150 sets of cases are
used as training data and testing data.
