Diagnosis System Using Case-Based Reasoning

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.