Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Applications of soft computing in ti...
~
SpringerLink (Online service)
Applications of soft computing in time series forecasting = simulation and modeling techniques /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Applications of soft computing in time series forecasting/ by Pritpal Singh.
Reminder of title:
simulation and modeling techniques /
Author:
Singh, Pritpal.
Published:
Cham :Springer International Publishing : : 2016.,
Description:
xxi, 158 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Engineering. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-26293-2
ISBN:
9783319262932
Applications of soft computing in time series forecasting = simulation and modeling techniques /
Singh, Pritpal.
Applications of soft computing in time series forecasting
simulation and modeling techniques /[electronic resource] :by Pritpal Singh. - Cham :Springer International Publishing :2016. - xxi, 158 p. :ill. (some col.), digital ;24 cm. - Studies in fuzziness and soft computing,v.3301434-9922 ;. - Studies in fuzziness and soft computing ;vol. 45..
This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations.
ISBN: 9783319262932
Standard No.: 10.1007/978-3-319-26293-2doiSubjects--Topical Terms:
561152
Engineering.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Applications of soft computing in time series forecasting = simulation and modeling techniques /
LDR
:02065nam a2200313 a 4500
001
860866
003
DE-He213
005
20160722113946.0
006
m d
007
cr nn 008maaau
008
170720s2016 gw s 0 eng d
020
$a
9783319262932
$q
(electronic bk.)
020
$a
9783319262925
$q
(paper)
024
7
$a
10.1007/978-3-319-26293-2
$2
doi
035
$a
978-3-319-26293-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
Q342
072
7
$a
UYQ
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
082
0 4
$a
006.3
$2
23
090
$a
Q342
$b
.S617 2016
100
1
$a
Singh, Pritpal.
$3
1102809
245
1 0
$a
Applications of soft computing in time series forecasting
$h
[electronic resource] :
$b
simulation and modeling techniques /
$c
by Pritpal Singh.
260
$a
Cham :
$c
2016.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
xxi, 158 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Studies in fuzziness and soft computing,
$x
1434-9922 ;
$v
v.330
520
$a
This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations.
650
0
$a
Engineering.
$3
561152
650
0
$a
Artificial intelligence.
$3
559380
650
0
$a
Computer simulation.
$3
560190
650
0
$a
Statistical physics.
$3
528048
650
0
$a
Computational intelligence.
$3
568984
650
2 4
$a
Nonlinear Dynamics.
$3
783150
650
2 4
$a
Simulation and Modeling.
$3
669249
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
593924
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Studies in fuzziness and soft computing ;
$v
vol. 45.
$3
839637
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-26293-2
950
$a
Engineering (Springer-11647)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login