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Uncertain information and linear systems / by Tofigh Allahviranloo

By: Allahviranloo, Tofigh, autor
Series: (Studies in Systems Decision and Control, 2198-4182 ; 254); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Cham : Springer International Publishing, 2020Edition: First edition.Description: 1 recurso en línea (X, 257 páginas).ISBN: 9783030313241.Subject: Incertidumbre (Teoría de la información) | Sistemas linealesOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Uncertainty -- Uncertain Linear systems -- Linear equations with advanced uncertainty.
Abstract: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q375 2020 EB (Browse shelf(Opens below)) Acceso electrónico eBook07112025
Total holds: 0

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.

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