國立高雄大學圖資館 |

Language: English

Back

Applications of soft computing in ti...

Singh, Pritpal.

Applications of soft computing in time series forecastingsimulation and modeling techniques /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applications of soft computing in time series forecastingby 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$q(electronic bk.)

Applications of soft computing in time series forecastingsimulation and modeling techniques /
Singh, Pritpal.

Applications of soft computing in time series forecastingsimulation 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 ;v.273..

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$q(electronic bk.)

Standard No.: 10.1007/978-3-319-26293-2doiSubjects--Topical Terms:

210888
Engineering.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Applications of soft computing in time series forecastingsimulation and modeling techniques /
LDR:02065nmm a2200313 a 4500 001 481659
003 DE-He213
005 20160722113946.0
006 m d
007 cr nn 008maaau
008 161007s2016 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 737832
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 : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
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 210888
650 0 $a Artificial intelligence. $3 194058
650 0 $a Computer simulation. $3 182122
650 0 $a Statistical physics. $3 183716
650 0 $a Computational intelligence. $3 210824
650 2 4 $a Nonlinear Dynamics. $3 492213
650 2 4 $a Simulation and Modeling. $3 273719
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Studies in fuzziness and soft computing ; $v v.273. $3 558583
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-26293-2
950 $a Engineering (Springer-11647)