A fusion of Bayesian and fuzzy analysis for print faults diagnosis, http://best.me.berkeley.edu/~aagogino/papers/ISCA-Fusion.pdf

logic, Bayesian network, diagnosis This paper is part of a larger study of remote print defect diagnosis. The goals of the integrated print defect diagnosis system are to reduce diagnosis time, streamline communication between customers and call center personnel, increase print defect handling efficiency and boost customer satisfaction through improved service. In this paper, we aggregate the information stemming from two diagnostic tools – Bayesian belief networks and fuzzy logic – to arrive at a more robust diagnostic result than possible from either tool alone. 1