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Biological Models via Interval Type-2 Fuzzy Sets / by Rosana Sueli da Motta Jafelice, Ana Maria Amarillo Bertone
(SpringerBriefs in Mathematics. ISSN:21918201)

1st ed. 2021.
出版者 (Cham : Springer International Publishing : Imprint: Springer)
出版年 2021
大きさ XVIII, 136 p. 90 illus., 87 illus. in color : online resource
著者標目 *Jafelice, Rosana Sueli da Motta author
Amarillo Bertone, Ana Maria author
SpringerLink (Online service)
件 名 LCSH:Biomathematics
LCSH:Set theory
LCSH:Computer simulation
FREE:Mathematical and Computational Biology
FREE:Set Theory
FREE:Computer Modelling
一般注記 - Introduction -- A Tour of Type-1 and Interval Type-2 Fuzzy Sets Theory -- Interval Type-2 Fuzzy Rule-Based System Applications -- Interval Type-2 Fuzzy Sets in the Future: Scientific Projects for Development -- Index
This book offers a gentle introduction to type-2 fuzzy sets and, in particular, interval type-2 fuzzy sets and their application in biological modeling. Interval type-2 fuzzy modeling is a comparatively recent direction of research in fuzzy modeling. As the modeling of biological problems is inherently uncertain, the use of fuzzy sets in this field is a natural choice. The coverage begins with a succinct review of type-1 fuzzy basic theory, before providing a comprehensive and didactic explanation of type-2 fuzzy set components. In turn, Fuzzy Rule-Based Systems, or FRBS, are shown for both types, interval type-2 and type-1 fuzzy sets. Applications include the pharmacological models, prediction of prostate cancer stages, a model for HIV population transfer (asymptomatic to symptomatic), an epidemiological disease caused by HIV, some models in population growth, included the Malthus Model, and an epidemic model refers to COVID-19. The book is ideally suited to graduate students in mathematics and related fields, professionals, researchers, or the public interested in interval type-2 fuzzy modeling. Largely self-contained, it can also be used as a supplementary text in specialized graduate courses
HTTP:URL=https://doi.org/10.1007/978-3-030-64530-4
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Springer eBooks 9783030645304
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データ種別 電子ブック
分 類 LCC:QH323.5
LCC:QH324.2-324.25
DC23:570.285
書誌ID 4000135571
ISBN 9783030645304

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