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New Paradigms in Computational Modeling and Its Applications
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New Paradigms in Computational Modeling and Its Applications

Book Details

Format Paperback / Softback
ISBN-10 012822133X
ISBN-13 9780128221334
Publisher Elsevier Science Publishing Co Inc
Imprint Academic Press Inc
Country of Manufacture NL
Country of Publication GB
Publication Date Jan 16th, 2021
Print length 278 Pages
Weight 586 grams
Dimensions 19.20 x 23.40 x 2.20 cms
Product Classification: Biomedical engineering
Ksh 23,600.00
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In general, every problem of science and engineering is governed by mathematical models. There is often a need to model, solve and interpret the problems one encounters in the world of practical problems. Models of practical application problems usually need to be handled by efficient computational models. New Paradigms in Computational Modeling and Its Applications deals with recent developments in mathematical methods, including theoretical models as well as applied science and engineering. The book focuses on subjects that can benefit from mathematical methods with concepts of simulation, waves, dynamics, uncertainty, machine intelligence, and applied mathematics. The authors bring together leading-edge research on mathematics combining various fields of science and engineering. This perspective acknowledges the inherent characteristic of current research on mathematics operating in parallel over different subject fields. New Paradigms in Computational Modeling and Its Applications meets the present and future needs for the interaction between various science and technology/engineering areas on the one hand and different branches of mathematics on the other. As such, the book contains 13 chapters covering various aspects of computational modeling from theoretical to application problems. The first six chapters address various problems of structural and fluid dynamics. The next four chapters include solving problems where the governing parameters are uncertain regarding fuzzy, interval, and affine. The final three chapters will be devoted to the use of machine intelligence in artificial neural networks.

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