Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Combining Interval, Probabilistic, a...
~
SpringerLink (Online service)
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications/ by Andrew Pownuk, Vladik Kreinovich.
Author:
Pownuk, Andrew.
other author:
Kreinovich, Vladik.
Description:
XI, 202 p. 2 illus., 1 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Computational intelligence. -
Online resource:
https://doi.org/10.1007/978-3-319-91026-0
ISBN:
9783319910260
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
Pownuk, Andrew.
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
[electronic resource] /by Andrew Pownuk, Vladik Kreinovich. - 1st ed. 2018. - XI, 202 p. 2 illus., 1 illus. in color.online resource. - Studies in Computational Intelligence,7731860-949X ;. - Studies in Computational Intelligence,564.
Introduction -- How to Get More Accurate Estimates -- How to Speed Up Computations -- Towards a Better Understandability of Uncertainty-Estimating Algorithms -- How General Can We Go: What Is Computable and What Is Not -- Decision Making Under Uncertainty -- Conclusions.
How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty. .
ISBN: 9783319910260
Standard No.: 10.1007/978-3-319-91026-0doiSubjects--Topical Terms:
568984
Computational intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
LDR
:02800nam a22004095i 4500
001
993169
003
DE-He213
005
20200704044817.0
007
cr nn 008mamaa
008
201225s2018 gw | s |||| 0|eng d
020
$a
9783319910260
$9
978-3-319-91026-0
024
7
$a
10.1007/978-3-319-91026-0
$2
doi
035
$a
978-3-319-91026-0
050
4
$a
Q342
072
7
$a
UYQ
$2
bicssc
072
7
$a
TEC009000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
006.3
$2
23
100
1
$a
Pownuk, Andrew.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1204818
245
1 0
$a
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
$h
[electronic resource] /
$c
by Andrew Pownuk, Vladik Kreinovich.
250
$a
1st ed. 2018.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
XI, 202 p. 2 illus., 1 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Studies in Computational Intelligence,
$x
1860-949X ;
$v
773
505
0
$a
Introduction -- How to Get More Accurate Estimates -- How to Speed Up Computations -- Towards a Better Understandability of Uncertainty-Estimating Algorithms -- How General Can We Go: What Is Computable and What Is Not -- Decision Making Under Uncertainty -- Conclusions.
520
$a
How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty. .
650
0
$a
Computational intelligence.
$3
568984
650
0
$a
Engineering mathematics.
$3
562757
650
1 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Engineering Mathematics.
$3
1203947
700
1
$a
Kreinovich, Vladik.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
964800
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783319910253
776
0 8
$i
Printed edition:
$z
9783319910277
776
0 8
$i
Printed edition:
$z
9783030081584
830
0
$a
Studies in Computational Intelligence,
$x
1860-949X ;
$v
564
$3
1253640
856
4 0
$u
https://doi.org/10.1007/978-3-319-91026-0
912
$a
ZDB-2-ENG
912
$a
ZDB-2-SXE
950
$a
Engineering (SpringerNature-11647)
950
$a
Engineering (R0) (SpringerNature-43712)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login