By Topic

An efficient and practical diagnosis model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yue Xu ; Sch. of Math. Stat. & Comput. Sci., New England Univ., Armidale, NSW, Australia ; Chenggi Zhang

The task of diagnosis, a typical abductive problem, as to find a hypothesis that best explains a set of observations. Generally, a neural network diagnostic reasoning model finds only one hypothesis to a set of observations. It is computationally expensive to find the hypothesis because the number of the potential hypotheses is exponentially large. Recently, we have proposed a connectionist diagnosis model to overcome the above difficulty. In this paper, we propose a method to improve the efficiency and the practicality of the model. The improved model can find more solutions, and the efficiency of the model is also improved

Published in:

Tools with Artificial Intelligence, 1998. Proceedings. Tenth IEEE International Conference on

Date of Conference:

10-12 Nov 1998