Critical developments and applications of swarm intelligence:
"This book provides innovative findings in swarm intelligence, evolutionary computation, computational intelligence, optimization techniques, and their applications"--
Gespeichert in:
Weitere Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
[2018]
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | "This book provides innovative findings in swarm intelligence, evolutionary computation, computational intelligence, optimization techniques, and their applications"-- |
Beschreibung: | 25 PDFs (xxiv, 478 pages) Also available in print. |
Format: | Mode of access: World Wide Web. |
Bibliographie: | Includes bibliographical references and index. |
ISBN: | 9781522551355 |
Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
LEADER | 00000nam a2200000 i 4500 | ||
---|---|---|---|
001 | ZDB-98-IGB-00187078 | ||
003 | IGIG | ||
005 | 20180207165529.0 | ||
006 | m eo d | ||
007 | cr bn |||m|||a | ||
008 | 180208s2018 pau fob 001 0 eng d | ||
010 | |z 2017035978 | ||
020 | |a 9781522551355 |q eISBN | ||
020 | |z 9781522551348 |q h/c | ||
024 | 7 | |a 10.4018/978-1-5225-5134-8 |2 doi | |
035 | |a (CaBNVSL)slc19857394 | ||
035 | |a (OCoLC)1022579398 | ||
040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
050 | 4 | |a Q337.3 |b .C75 2018e | |
082 | 7 | |a 006.3/824 |2 23 | |
245 | 0 | 0 | |a Critical developments and applications of swarm intelligence |c Yuhui Shi, editor. |
264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c [2018] | |
300 | |a 25 PDFs (xxiv, 478 pages) | ||
336 | |a text |2 rdacontent | ||
337 | |a electronic |2 isbdmedia | ||
338 | |a online resource |2 rdacarrier | ||
504 | |a Includes bibliographical references and index. | ||
505 | 0 | |a Section 1. Swarm intelligence algorithms. Chapter 1. Unified swarm intelligence algorithms ; Chapter 2. Local best particle swarm optimization using crown jewel defense strategy ; Chapter 3. Multi-objective binary fish school search ; Chapter 4. City group optimization: an optimizer for continuous problems ; Chapter 5. Magnetotactic bacteria optimization algorithm (MBOA) for function optimization: MBOA based on four best-Rand pairwise schemes ; Chapter 6. An analysis on fireworks algorithm solving problems with shifts in the decision space and objective space -- Section 2. Swarm intelligence applications. Chapter 7. Assessment of gamma-ray-spectra analysis method utilizing the fireworks algorithm for various error measures ; Chapter 8. A computational comparison of swarm optimization techniques for optimal load shedding under the presence of FACTS devices to avoid voltage instability ; Chapter 9. Using particle swarm optimization algorithm as an optimization tool within developed neural networks ; Chapter 10. Squeeze casting parameter optimization using swarm intelligence and evolutionary algorithms ; Chapter 11. Swarm-intelligence-based communication protocols for wireless sensor networks ; Chapter 12. Image reconstruction of electrical impedance tomography using fish school search and differential evolution ; Chapter 13. Multi-thresholding of histopathological images using fuzzy entropy and parameterless cuckoo search ; Chapter 14. Optimized base station sleeping and smart grid energy procurement scheme to improve energy efficiency ; Chapter 15. Using cuckoo search algorithm for hybrid flow shop scheduling problems under makespan criterion ; Chapter 16. Particle swarm optimization for model predictive control in reinforcement learning environments. | |
506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
520 | 3 | |a "This book provides innovative findings in swarm intelligence, evolutionary computation, computational intelligence, optimization techniques, and their applications"-- |c Provided by publisher. | |
530 | |a Also available in print. | ||
538 | |a Mode of access: World Wide Web. | ||
588 | |a Description based on title screen (IGI Global, viewed 02/08/2018). | ||
650 | 0 | |a Swarm intelligence. | |
700 | 1 | |a Shi, Yuhui, |e editor. | |
710 | 2 | |a IGI Global, |e publisher. | |
776 | 0 | |c (Original) |w (DLC)2017035978 | |
776 | 0 | 8 | |i Print version: |z 1522551344 |z 9781522551348 |w (DLC) 2017035978 |
856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5134-8 |3 Volltext |
912 | |a ZDB-98-IGB | ||
049 | |a DE-863 |
Datensatz im Suchindex
DE-BY-FWS_katkey | ZDB-98-IGB-00187078 |
---|---|
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adam_text | |
any_adam_object | |
author2 | Shi, Yuhui |
author2_role | edt |
author2_variant | y s ys |
author_facet | Shi, Yuhui |
building | Verbundindex |
bvnumber | localFWS |
callnumber-first | Q - Science |
callnumber-label | Q337 |
callnumber-raw | Q337.3 .C75 2018e |
callnumber-search | Q337.3 .C75 2018e |
callnumber-sort | Q 3337.3 C75 42018E |
callnumber-subject | Q - General Science |
collection | ZDB-98-IGB |
contents | Section 1. Swarm intelligence algorithms. Chapter 1. Unified swarm intelligence algorithms ; Chapter 2. Local best particle swarm optimization using crown jewel defense strategy ; Chapter 3. Multi-objective binary fish school search ; Chapter 4. City group optimization: an optimizer for continuous problems ; Chapter 5. Magnetotactic bacteria optimization algorithm (MBOA) for function optimization: MBOA based on four best-Rand pairwise schemes ; Chapter 6. An analysis on fireworks algorithm solving problems with shifts in the decision space and objective space -- Section 2. Swarm intelligence applications. Chapter 7. Assessment of gamma-ray-spectra analysis method utilizing the fireworks algorithm for various error measures ; Chapter 8. A computational comparison of swarm optimization techniques for optimal load shedding under the presence of FACTS devices to avoid voltage instability ; Chapter 9. Using particle swarm optimization algorithm as an optimization tool within developed neural networks ; Chapter 10. Squeeze casting parameter optimization using swarm intelligence and evolutionary algorithms ; Chapter 11. Swarm-intelligence-based communication protocols for wireless sensor networks ; Chapter 12. Image reconstruction of electrical impedance tomography using fish school search and differential evolution ; Chapter 13. Multi-thresholding of histopathological images using fuzzy entropy and parameterless cuckoo search ; Chapter 14. Optimized base station sleeping and smart grid energy procurement scheme to improve energy efficiency ; Chapter 15. Using cuckoo search algorithm for hybrid flow shop scheduling problems under makespan criterion ; Chapter 16. Particle swarm optimization for model predictive control in reinforcement learning environments. |
ctrlnum | (CaBNVSL)slc19857394 (OCoLC)1022579398 |
dewey-full | 006.3/824 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.3/824 |
dewey-search | 006.3/824 |
dewey-sort | 16.3 3824 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
format | Electronic eBook |
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id | ZDB-98-IGB-00187078 |
illustrated | Not Illustrated |
indexdate | 2024-11-26T14:51:53Z |
institution | BVB |
isbn | 9781522551355 |
language | English |
oclc_num | 1022579398 |
open_access_boolean | |
owner | DE-863 DE-BY-FWS |
owner_facet | DE-863 DE-BY-FWS |
physical | 25 PDFs (xxiv, 478 pages) Also available in print. |
psigel | ZDB-98-IGB |
publishDate | 2018 |
publishDateSearch | 2018 |
publishDateSort | 2018 |
publisher | IGI Global, |
record_format | marc |
spelling | Critical developments and applications of swarm intelligence Yuhui Shi, editor. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, [2018] 25 PDFs (xxiv, 478 pages) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Section 1. Swarm intelligence algorithms. Chapter 1. Unified swarm intelligence algorithms ; Chapter 2. Local best particle swarm optimization using crown jewel defense strategy ; Chapter 3. Multi-objective binary fish school search ; Chapter 4. City group optimization: an optimizer for continuous problems ; Chapter 5. Magnetotactic bacteria optimization algorithm (MBOA) for function optimization: MBOA based on four best-Rand pairwise schemes ; Chapter 6. An analysis on fireworks algorithm solving problems with shifts in the decision space and objective space -- Section 2. Swarm intelligence applications. Chapter 7. Assessment of gamma-ray-spectra analysis method utilizing the fireworks algorithm for various error measures ; Chapter 8. A computational comparison of swarm optimization techniques for optimal load shedding under the presence of FACTS devices to avoid voltage instability ; Chapter 9. Using particle swarm optimization algorithm as an optimization tool within developed neural networks ; Chapter 10. Squeeze casting parameter optimization using swarm intelligence and evolutionary algorithms ; Chapter 11. Swarm-intelligence-based communication protocols for wireless sensor networks ; Chapter 12. Image reconstruction of electrical impedance tomography using fish school search and differential evolution ; Chapter 13. Multi-thresholding of histopathological images using fuzzy entropy and parameterless cuckoo search ; Chapter 14. Optimized base station sleeping and smart grid energy procurement scheme to improve energy efficiency ; Chapter 15. Using cuckoo search algorithm for hybrid flow shop scheduling problems under makespan criterion ; Chapter 16. Particle swarm optimization for model predictive control in reinforcement learning environments. Restricted to subscribers or individual electronic text purchasers. "This book provides innovative findings in swarm intelligence, evolutionary computation, computational intelligence, optimization techniques, and their applications"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 02/08/2018). Swarm intelligence. Shi, Yuhui, editor. IGI Global, publisher. (Original) (DLC)2017035978 Print version: 1522551344 9781522551348 (DLC) 2017035978 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5134-8 Volltext |
spellingShingle | Critical developments and applications of swarm intelligence Section 1. Swarm intelligence algorithms. Chapter 1. Unified swarm intelligence algorithms ; Chapter 2. Local best particle swarm optimization using crown jewel defense strategy ; Chapter 3. Multi-objective binary fish school search ; Chapter 4. City group optimization: an optimizer for continuous problems ; Chapter 5. Magnetotactic bacteria optimization algorithm (MBOA) for function optimization: MBOA based on four best-Rand pairwise schemes ; Chapter 6. An analysis on fireworks algorithm solving problems with shifts in the decision space and objective space -- Section 2. Swarm intelligence applications. Chapter 7. Assessment of gamma-ray-spectra analysis method utilizing the fireworks algorithm for various error measures ; Chapter 8. A computational comparison of swarm optimization techniques for optimal load shedding under the presence of FACTS devices to avoid voltage instability ; Chapter 9. Using particle swarm optimization algorithm as an optimization tool within developed neural networks ; Chapter 10. Squeeze casting parameter optimization using swarm intelligence and evolutionary algorithms ; Chapter 11. Swarm-intelligence-based communication protocols for wireless sensor networks ; Chapter 12. Image reconstruction of electrical impedance tomography using fish school search and differential evolution ; Chapter 13. Multi-thresholding of histopathological images using fuzzy entropy and parameterless cuckoo search ; Chapter 14. Optimized base station sleeping and smart grid energy procurement scheme to improve energy efficiency ; Chapter 15. Using cuckoo search algorithm for hybrid flow shop scheduling problems under makespan criterion ; Chapter 16. Particle swarm optimization for model predictive control in reinforcement learning environments. Swarm intelligence. |
title | Critical developments and applications of swarm intelligence |
title_auth | Critical developments and applications of swarm intelligence |
title_exact_search | Critical developments and applications of swarm intelligence |
title_full | Critical developments and applications of swarm intelligence Yuhui Shi, editor. |
title_fullStr | Critical developments and applications of swarm intelligence Yuhui Shi, editor. |
title_full_unstemmed | Critical developments and applications of swarm intelligence Yuhui Shi, editor. |
title_short | Critical developments and applications of swarm intelligence |
title_sort | critical developments and applications of swarm intelligence |
topic | Swarm intelligence. |
topic_facet | Swarm intelligence. |
url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5134-8 |
work_keys_str_mv | AT shiyuhui criticaldevelopmentsandapplicationsofswarmintelligence AT igiglobal criticaldevelopmentsandapplicationsofswarmintelligence |