000 | 02933nam a22004935i 4500 | ||
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001 | 978-3-662-46309-3 | ||
003 | DE-He213 | ||
005 | 20200421112557.0 | ||
007 | cr nn 008mamaa | ||
008 | 150310s2015 gw | s |||| 0|eng d | ||
020 |
_a9783662463093 _9978-3-662-46309-3 |
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024 | 7 |
_a10.1007/978-3-662-46309-3 _2doi |
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050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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082 | 0 | 4 |
_a006.3 _223 |
245 | 1 | 0 |
_aMulti-objective Swarm Intelligence _h[electronic resource] : _bTheoretical Advances and Applications / _cedited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2015. |
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300 |
_aXIV, 201 p. 60 illus., 11 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aStudies in Computational Intelligence, _x1860-949X ; _v592 |
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505 | 0 | _aIntroduction -- 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 | _aThe 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 | _aEngineering. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
700 | 1 |
_aDehuri, Satchidananda. _eeditor. |
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700 | 1 |
_aJagadev, Alok Kumar. _eeditor. |
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700 | 1 |
_aPanda, Mrutyunjaya. _eeditor. |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783662463086 |
830 | 0 |
_aStudies in Computational Intelligence, _x1860-949X ; _v592 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-662-46309-3 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c59216 _d59216 |