MMM-CADIAG: A mini modified CADIAG with mobius transform
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DOI:
https://doi.org/10.15625/1813-9663/14/1/7877Abstract
This paper describes the MMM-CADIAG system called Mini Modifid CADIAG with Moebius transform which is based on the algorithm of Mobius transform for CADIAG-2. This algorithm using Mobius trasform to compute new rule base for CADIAG-2. To apply Mobius transform for CADIAG-2 means to find new weights of fuzzy rules. This algorithm guarantees that using generalized MaxMin inference of CADIAG-2 the inference machine will reproduce the expert’s stated conditional beliefs as total degrees of confirmation and exclusion. MMM-CADIAG uses positive and negative knowledge. Knowledge Base of the system consists of set of IF - THEN rules. Each rule assigns its weight in [0, 1], With assumption that relative frequencies are used as weights of rules. MMM-CADIAG is able to calculate new weights of fuzzy rules and then suggest diagnoses by using the Mini Modified inference engine of CADIAG-2. Finally, a computer test program with established simple knowledge base in Oriental Medicine as an example is developed and tested. Programs is developed in C++ programming language and can run on PC/IBM computers.Metrics
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Published
14-03-2016
How to Cite
[1]
N. H. Phương, “MMM-CADIAG: A mini modified CADIAG with mobius transform”, JCC, vol. 14, no. 1, pp. 9–18, Mar. 2016.
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Computer Science
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