|
|
|
|
LEADER |
02932nam a22004815i 4500 |
001 |
978-3-662-46309-3 |
003 |
DE-He213 |
005 |
20151030061202.0 |
007 |
cr nn 008mamaa |
008 |
150310s2015 gw | s |||| 0|eng d |
020 |
|
|
|a 9783662463093
|9 978-3-662-46309-3
|
024 |
7 |
|
|a 10.1007/978-3-662-46309-3
|2 doi
|
040 |
|
|
|d GrThAP
|
050 |
|
4 |
|a Q342
|
072 |
|
7 |
|a UYQ
|2 bicssc
|
072 |
|
7 |
|a COM004000
|2 bisacsh
|
082 |
0 |
4 |
|a 006.3
|2 23
|
245 |
1 |
0 |
|a Multi-objective Swarm Intelligence
|h [electronic resource] :
|b Theoretical Advances and Applications /
|c edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda.
|
264 |
|
1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2015.
|
300 |
|
|
|a XIV, 201 p. 60 illus., 11 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 592
|
505 |
0 |
|
|a Introduction -- Behavior of Bacterial Colony -- E.coli Bacterial Colonies -- Optimization based on E.coli Bacterial Colony -- Classification of BFO Algorithm -- Multi-objective optimization based on BF -- An overview of BFO Applications -- Conclusion.
|
520 |
|
|
|a The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO. .
|
650 |
|
0 |
|a Engineering.
|
650 |
|
0 |
|a Artificial intelligence.
|
650 |
|
0 |
|a Computational intelligence.
|
650 |
1 |
4 |
|a Engineering.
|
650 |
2 |
4 |
|a Computational Intelligence.
|
650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
|
700 |
1 |
|
|a Dehuri, Satchidananda.
|e editor.
|
700 |
1 |
|
|a Jagadev, Alok Kumar.
|e editor.
|
700 |
1 |
|
|a Panda, Mrutyunjaya.
|e editor.
|
710 |
2 |
|
|a SpringerLink (Online service)
|
773 |
0 |
|
|t Springer eBooks
|
776 |
0 |
8 |
|i Printed edition:
|z 9783662463086
|
830 |
|
0 |
|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 592
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-662-46309-3
|z Full Text via HEAL-Link
|
912 |
|
|
|a ZDB-2-ENG
|
950 |
|
|
|a Engineering (Springer-11647)
|