東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

NEO 2015 = results of the Numerical ...

Numerical and Evolutionary Optimization Workshop ((2015 :)

Linked to FindBook

Google Book

Amazon

博客來

NEO 2015 = results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico /

Record Type:	Electronic resources : Monograph/item
Title/Author:	NEO 2015/ edited by Oliver Schutze ... [et al.].
Reminder of title:	results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico /
other author:	Schutze, Oliver.
corporate name:	Numerical and Evolutionary Optimization Workshop
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xvi, 444 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Part I Genetic Programming -- Part II Combinatorial Optimization -- Part IV Machine Learning and Real World Applications.
Contained By:	Springer eBooks
Subject:	Mathematical optimization - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-319-44003-3
ISBN:	9783319440033

NEO 2015 = results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico /
NEO 2015results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico /[electronic resource] :edited by Oliver Schutze ... [et al.]. - Cham :Springer International Publishing :2017. - xvi, 444 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6631860-949X ;. - Studies in computational intelligence ;v.663..

Part I Genetic Programming -- Part II Combinatorial Optimization -- Part IV Machine Learning and Real World Applications.

This volume comprises a selection of works presented at the Numerical and Evolutionary Optimization (NEO) workshop held in September 2015 in Tijuana, Mexico. The development of powerful search and optimization techniques is of great importance in today's world that requires researchers and practitioners to tackle a growing number of challenging real-world problems. In particular, there are two well-established and widely known fields that are commonly applied in this area: (i) traditional numerical optimization techniques and (ii) comparatively recent bio-inspired heuristics. Both paradigms have their unique strengths and weaknesses, allowing them to solve some challenging problems while still failing in others. The goal of the NEO workshop series is to bring together people from these and related fields to discuss, compare and merge their complimentary perspectives in order to develop fast and reliable hybrid methods that maximize the strengths and minimize the weaknesses of the underlying paradigms. Through this effort, we believe that the NEO can promote the development of new techniques that are applicable to a broader class of problems. Moreover, NEO fosters the understanding and adequate treatment of real-world problems particularly in emerging fields that affect us all such as health care, smart cities, big data, among many others. The extended papers the NEO 2015 that comprise this book make a contribution to this goal.

ISBN: 9783319440033

Standard No.: 10.1007/978-3-319-44003-3doiSubjects--Topical Terms:

647613
Mathematical optimization
--Congresses.

LC Class. No.: QA402.5 / .N46 2015

Dewey Class. No.: 519.6

NEO 2015 = results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico /
LDR:02712nmm a2200337 a 4500 001 2190944
003 DE-He213
005 20191112172236.0
006 m d
007 cr nn 008maaau
008 200504s2017 gw s 0 eng d
020 $a 9783319440033 $q (electronic bk.)
020 $a 9783319440026 $q (paper)
024 7 $a 10.1007/978-3-319-44003-3 $2 doi
035 $a 978-3-319-44003-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA402.5 $b .N46 2015
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 519.6 $2 23
090 $a QA402.5 $b .N971 2015
111 2 $a Numerical and Evolutionary Optimization Workshop $d (2015 : $c Tijuana, Mexico) $3 3409937
245 1 0 $a NEO 2015 $h [electronic resource] : $b results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico / $c edited by Oliver Schutze ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xvi, 444 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.663
505 0 $a Part I Genetic Programming -- Part II Combinatorial Optimization -- Part IV Machine Learning and Real World Applications.
520 $a This volume comprises a selection of works presented at the Numerical and Evolutionary Optimization (NEO) workshop held in September 2015 in Tijuana, Mexico. The development of powerful search and optimization techniques is of great importance in today's world that requires researchers and practitioners to tackle a growing number of challenging real-world problems. In particular, there are two well-established and widely known fields that are commonly applied in this area: (i) traditional numerical optimization techniques and (ii) comparatively recent bio-inspired heuristics. Both paradigms have their unique strengths and weaknesses, allowing them to solve some challenging problems while still failing in others. The goal of the NEO workshop series is to bring together people from these and related fields to discuss, compare and merge their complimentary perspectives in order to develop fast and reliable hybrid methods that maximize the strengths and minimize the weaknesses of the underlying paradigms. Through this effort, we believe that the NEO can promote the development of new techniques that are applicable to a broader class of problems. Moreover, NEO fosters the understanding and adequate treatment of real-world problems particularly in emerging fields that affect us all such as health care, smart cities, big data, among many others. The extended papers the NEO 2015 that comprise this book make a contribution to this goal.
650 0 $a Mathematical optimization $x Congresses. $3 647613
650 0 $a Evolution equations $x Congresses. $3 659610
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Optimization. $3 891104
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Big Data/Analytics. $3 2186785
700 1 $a Schutze, Oliver. $3 3409938
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v.663. $3 3409939
856 4 0 $u https://doi.org/10.1007/978-3-319-44003-3
950 $a Engineering (Springer-11647)