國立高雄大學圖資館 |

Language: English

Back

Beyond traditional probabilistic dat...

Kosheleva, Olga.

Beyond traditional probabilistic data processing techniquesinterval, fuzzy etc. methods and their applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Beyond traditional probabilistic data processing techniquesedited by Olga Kosheleva ... [et al.].
Reminder of title:	interval, fuzzy etc. methods and their applications /
other author:	Kosheleva, Olga.
Published:	Cham :Springer International Publishing :2020.
Description:	xi, 649 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Fuzzy mathematics.
Online resource:	https://doi.org/10.1007/978-3-030-31041-7
ISBN:	9783030310417$q(electronic bk.)

Beyond traditional probabilistic data processing techniquesinterval, fuzzy etc. methods and their applications /
Beyond traditional probabilistic data processing techniquesinterval, fuzzy etc. methods and their applications /[electronic resource] :edited by Olga Kosheleva ... [et al.]. - Cham :Springer International Publishing :2020. - xi, 649 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,8351860-949X ;. - Studies in computational intelligence ;v. 216..

Symmetries are Important -- Constructive Continuity of Increasing Functions -- A Constructive Framework for Teaching Discrete Mathematics -- Fuzzy Logic for Incidence Geometry -- Strengths of Fuzzy Techniques in Data Science -- Impact of Time Delays on Networked Control of Autonomous Systems -- Sets and Systems -- An Overview of Polynomially Computable Characteristics of Special Interval Matrices -- Interval Regularization for Inaccurate Linear Algebraic Equations -- Measurable Process Selection Theorem and Non-Autonomous Inclusions -- Handling Uncertainty When Getting Contradictory Advice from Experts -- Why Sparse? -- The Kreinovich Temporal Universe -- Integral Transforms induced by Heaviside Perceptrons.

Data processing has become essential to modern civilization. The original data for this processing comes from measurements or from experts, and both sources are subject to uncertainty. Traditionally, probabilistic methods have been used to process uncertainty. However, in many practical situations, we do not know the corresponding probabilities: in measurements, we often only know the upper bound on the measurement errors; this is known as interval uncertainty. In turn, expert estimates often include imprecise (fuzzy) words from natural language such as "small"; this is known as fuzzy uncertainty. In this book, leading specialists on interval, fuzzy, probabilistic uncertainty and their combination describe state-of-the-art developments in their research areas. Accordingly, the book offers a valuable guide for researchers and practitioners interested in data processing under uncertainty, and an introduction to the latest trends and techniques in this area, suitable for graduate students.

ISBN: 9783030310417$q(electronic bk.)

Standard No.: 10.1007/978-3-030-31041-7doiSubjects--Topical Terms:

243725
Fuzzy mathematics.

LC Class. No.: QA248.5 / .B496 2020

Dewey Class. No.: 519.5

Beyond traditional probabilistic data processing techniquesinterval, fuzzy etc. methods and their applications /
LDR:02888nmm a2200349 a 4500 001 574981
003 DE-He213
005 20200714172801.0
006 m d
007 cr nn 008maaau
008 201016s2020 sz s 0 eng d
020 $a 9783030310417$q(electronic bk.)
020 $a 9783030310400$q(paper)
024 7 $a 10.1007/978-3-030-31041-7 $2 doi
035 $a 978-3-030-31041-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA248.5 $b .B496 2020
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
072 7 $a TB $2 thema
082 0 4 $a 519.5 $2 23
090 $a QA248.5 $b .B573 2020
245 0 0 $a Beyond traditional probabilistic data processing techniques $h [electronic resource] : $b interval, fuzzy etc. methods and their applications / $c edited by Olga Kosheleva ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xi, 649 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v 835
505 0 $a Symmetries are Important -- Constructive Continuity of Increasing Functions -- A Constructive Framework for Teaching Discrete Mathematics -- Fuzzy Logic for Incidence Geometry -- Strengths of Fuzzy Techniques in Data Science -- Impact of Time Delays on Networked Control of Autonomous Systems -- Sets and Systems -- An Overview of Polynomially Computable Characteristics of Special Interval Matrices -- Interval Regularization for Inaccurate Linear Algebraic Equations -- Measurable Process Selection Theorem and Non-Autonomous Inclusions -- Handling Uncertainty When Getting Contradictory Advice from Experts -- Why Sparse? -- The Kreinovich Temporal Universe -- Integral Transforms induced by Heaviside Perceptrons.
520 $a Data processing has become essential to modern civilization. The original data for this processing comes from measurements or from experts, and both sources are subject to uncertainty. Traditionally, probabilistic methods have been used to process uncertainty. However, in many practical situations, we do not know the corresponding probabilities: in measurements, we often only know the upper bound on the measurement errors; this is known as interval uncertainty. In turn, expert estimates often include imprecise (fuzzy) words from natural language such as "small"; this is known as fuzzy uncertainty. In this book, leading specialists on interval, fuzzy, probabilistic uncertainty and their combination describe state-of-the-art developments in their research areas. Accordingly, the book offers a valuable guide for researchers and practitioners interested in data processing under uncertainty, and an introduction to the latest trends and techniques in this area, suitable for graduate students.
650 0 $a Fuzzy mathematics. $3 243725
650 0 $a Uncertainty (Information theory) $3 206405
650 1 4 $a Data Engineering. $3 839346
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
700 1 $a Kosheleva, Olga. $3 801376
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v. 216. $3 380871
856 4 0 $u https://doi.org/10.1007/978-3-030-31041-7
950 $a Intelligent Technologies and Robotics (Springer-42732)