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Uncertain information and linear systems
~
Allahviranloo, Tofigh.
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Uncertain information and linear systems
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Uncertain information and linear systems/ by Tofigh Allahviranloo.
作者:
Allahviranloo, Tofigh.
出版者:
Cham :Springer International Publishing : : 2020.,
面頁冊數:
x, 257 p. :ill., digital ;24 cm.
內容註:
Introduction -- Uncertainty -- Uncertain Linear systems -- Linear equations with advanced uncertainty.
Contained By:
Springer eBooks
標題:
Uncertainty (Information theory) -
電子資源:
https://doi.org/10.1007/978-3-030-31324-1
ISBN:
9783030313241
Uncertain information and linear systems
Allahviranloo, Tofigh.
Uncertain information and linear systems
[electronic resource] /by Tofigh Allahviranloo. - Cham :Springer International Publishing :2020. - x, 257 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.2542198-4182 ;. - Studies in systems, decision and control ;v.254..
Introduction -- Uncertainty -- Uncertain Linear systems -- Linear equations with advanced uncertainty.
This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.
ISBN: 9783030313241
Standard No.: 10.1007/978-3-030-31324-1doiSubjects--Topical Terms:
587701
Uncertainty (Information theory)
LC Class. No.: Q375
Dewey Class. No.: 003.54
Uncertain information and linear systems
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This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.
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