國立虎尾科技大學 |

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic/ by Patricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo.
作者:	Melin, Patricia.
其他作者:	Ontiveros-Robles, Emanuel.
面頁冊數:	VIII, 78 p. 76 illus., 74 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-75097-8
ISBN:	9783030750978

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic
Melin, Patricia.

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic[electronic resource] /by Patricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. - 1st ed. 2021. - VIII, 78 p. 76 illus., 74 illus. in color.online resource. - SpringerBriefs in Computational Intelligence,2625-3712. - SpringerBriefs in Computational Intelligence,.

Introduction -- Background and theory -- Proposed Methodology -- Experimental Results -- Results discussion -- Conclusions.

This book presents different experimental results as evidence of the good results obtained compared with respect to conventional approaches and literature references based on fuzzy logic. Nowadays, the evolution of intelligence systems for decision making has been reached considerable levels of success, as these systems are getting more intelligent and can be of great help to experts in decision making. One of the more important realms in decision making is the area of medical diagnosis, and many kinds of intelligence systems provide the expert good assistance to perform diagnosis; some of these methods are, for example, artificial neural networks (can be very powerful to find tendencies), support vector machines, that avoid overfitting problems, and statistical approaches (e.g., Bayesian). However, the present research is focused on one of the most relevant kinds of intelligent systems, which are the fuzzy systems. The main objective of the present work is the generation of fuzzy diagnosis systems that offer competitive classifiers to be applied in diagnosis systems. To generate these systems, we have proposed a methodology for the automatic design of classifiers and is focused in the Generalized Type-2 Fuzzy Logic, because the uncertainty handling can provide us with the robustness necessary to be competitive with other kinds of methods. In addition, different alternatives to the uncertainty modeling, rules-selection, and optimization have been explored. Besides, different experimental results are presented as evidence of the good results obtained when compared with respect to conventional approaches and literature references based on Fuzzy Logic.

ISBN: 9783030750978

Standard No.: 10.1007/978-3-030-75097-8doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic
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