Fuzzy integral be applied to the diagnosis of gestational diabetes mellitus

Authors:
Caipo Zhang;Jinjie Song;Zhilong Wu
Affiliations:
Tianjin Key Laboratory of Intelligent Computing & Novel Software Techn., Tianjin Univ. of Technology, Tianjin, China and Key Laboratory of Computer Vision and System, Ministry of Education, Ti ...;Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology, Tianjin Univ. of Technology, Tianjin, China and Key Laboratory of Computer Vision and System, Ministry of Education ...;Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology, Tianjin Univ. of Technology, Tianjin, China and Key Laboratory of Computer Vision and System, Ministry of Education ...
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Year:
2009

Citing 4
Cited 0

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Abstract

This paper will use fuzzy integral to structure the diagnostic model of gestational diabetes mellitus. The Sugeno measure is obtained by training of BP neural network. The BP neural network is easy to get into local optimum, so the algorithm of simulated annealing is used to optimize the BP neural network, and it will obtain an approximate global optimal solution. In this diagnostic model, there are two key factors. One is the degree of fit that the degrees of evidential support for attribute that diagnostic object is gestational diabetes mellitus. The other is the importance of attribute itself. The instances of diabetes illuminate that the method is effective.