Uncertain Information and Linear Systems: 254 (Studies in Systems, Decision and Control, 254) - Image 1

£76.76

Springer Uncertain Information and Linear Systems: 254 (Studies in Systems, Decision and Control, 254)

Name: Uncertain Information and Linear Systems: 254 (Studies in Systems, Decision and Control, 254)
Brand: Springer
Price: 76.77 GBP
Availability: InStock

AI & Machine Learning

Price History & Forecast

Last 33 days • 33 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 33 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £77 (22 days, 66.7%)

Price range: £75 - £77

Price levels: 2 different prices over 33 days

Description

Product Description 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. Review “The book is well organized and presents the most important notions of uncertain information and linear systems. The book is suitable for senior undergraduate students as well as practical engineers, scientist and researchers interested in uncertain information and linear systems.” (Seenith Sivasundaram, zbMATH 1431.93002, 2020) From the Back Cover 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. About the Author Tofigh Allahviranloo is a Senior Full Professor of Applied Mathematics at Bahcesehir International University (BAU). As a mathematician and computer scientist, Tofigh has developed a passion for multi- and interdisciplinary research. He not only pursues fundamental research in fuzzy applied mathematics, especially fuzzy differential equations, but also develops innovative applications in the applied biological sciences. He is a prolific author, with a bibliography comprising over 200 peer-reviewed journal papers, 11 books in Farsi, 3 book chapters, and 20 contributions to conference proceedings, accumulating close to 6000 Google Scholar citations (h-index 40). Tofigh actively serves the research community, in particular as editor-in-chief of the International Journal of Industrial Mathematics and as a member of the editorial board of several other journals, including Fuzzy Sets and Systems, the Journal of Intelligent and Fuzzy Systems, and Mathematical Science.

Product Specifications

Brand: Springer
Format: Hardcover
ASIN: 3030313239
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 07 October 2019
Listed Since: 15 August 2019

Barcode

No barcode data available

Springer Uncertain Information and Linear Systems: 254 (Studies in Systems, Decision and Control, 254)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Multicriteria Decision-Making Under Conditions of Uncertainty: A Fuzzy Set Perspective

Uncertainty in Information Systems: An Introduction to Techniques and Applications (Advanced Topics in Computer Science)

Type-2 Fuzzy Logic: Uncertain Systems’ Modeling and Control (Nonlinear Physical Science)

Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications: 773 (Studies in Computational Intelligence, 773)

Analysis and Decision Making in Uncertain Systems (Communications and Control Engineering)

Towards Intelligent Engineering and Information Technology: 243 (Studies in Computational Intelligence, 243)

Modeling, Design, and Simulation of Systems with Uncertainties (Mathematical Engineering)

Robust Control of Linear Systems Subject to Uncertain Time-Varying Parameters: 325 (Lecture Notes in Control and Information Sciences, 325)

Flexible and Generalized Uncertainty Optimization: Theory and Approaches: 696 (Studies in Computational Intelligence, 696)

Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion: 15 (Studies in Systems, Decision and Control, 15)

Techniques of Decision Making, Uncertain Reasoning and Regression Analysis Under the Hesitant Fuzzy Environment and Their Applications (Uncertainty and Operations Research)

Towards Intelligent Systems Modeling and Simulation: With Applications to Energy, Epidemiology and Risk Assessment: 383 (Studies in Systems, Decision and Control, 383)

Intelligent Systems in Oil Field Development under Uncertainty: 183 (Studies in Computational Intelligence, 183)

Springer - The Mathematics of the Uncertain - Pedro Gil 142

Springer Mathematics of Uncertainty: Grand Challenges Book

Springer - Modeling, Design, and Simulation of Systems

Blind Identification of Structured Dynamic Systems: A Deterministic Perspective

Recent Advances in Applications of Computational and Fuzzy Mathematics

Stability and Control of Linear Systems: 185 (Studies in Systems, Decision and Control, 185)

Stochastic Systems: Uncertainty Quantification and Propagation (Springer Series in Reliability Engineering)

A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics: Theory and Applications: 347 (Studies in Fuzziness and Soft Computing, 347)

Piecewise Linear Control Systems: A Computational Approach: 284 (Lecture Notes in Control and Information Sciences, 284)

Fuzzy Differential Equations and Applications for Engineers and Scientists

Uncertainty Modelling in Data Science: 832 (Advances in Intelligent Systems and Computing, 832)