Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems:
"This book explores various concepts, principles, and applications of swarm intelligence algorithms"--
Gespeichert in:
Weitere Verfasser: | , |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
[2020]
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | "This book explores various concepts, principles, and applications of swarm intelligence algorithms"-- |
Beschreibung: | 22 PDFs (482 pages) Also available in print. |
Format: | Mode of access: World Wide Web. |
Bibliographie: | Includes bibliographical references and index. |
ISBN: | 9781799832249 |
Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
LEADER | 00000nam a2200000 i 4500 | ||
---|---|---|---|
001 | ZDB-98-IGB-00240813 | ||
003 | IGIG | ||
005 | 20200421161945.0 | ||
006 | m eo d | ||
007 | cr bn |||m|||a | ||
008 | 200422s2020 pau fob 001 0 eng d | ||
010 | |z 2019049634 | ||
020 | |a 9781799832249 |q ebook | ||
020 | |z 1799832244 | ||
020 | |z 9781799832225 |q hardcover | ||
020 | |z 9781799832232 |q paperback | ||
024 | 7 | |a 10.4018/978-1-7998-3222-5 |2 doi | |
035 | |a (CaBNVSL)slc00000445 | ||
035 | |a (OCoLC)1128061785 | ||
040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
050 | 4 | |a Q337.3 |b .H36 2020e | |
082 | 7 | |a 006.3/824 |2 23 | |
245 | 0 | 0 | |a Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems |c Shi Cheng and Yuhui Shi, editors. |
264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c [2020] | |
300 | |a 22 PDFs (482 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 | 2 | |a Chapter 1. Newly-developed swarm intelligence algorithms applied to renewable energy-based load dispatch real-world problems -- Chapter 2. Semi-automatic sensor ontology matching based on interactive multi-objective evolutionary -- Chapter 3. A comparative study among recursive metaheuristics for gene selection -- Chapter 4. Training artificial neural networks with improved particle swarm optimization: case of electricity demand forecasting in Thailand -- Chapter 5. Segmentation and edge extraction of grayscale images using firefly and artificial bee colony agorithms -- Chapter 6. Analysis of the dynamic characteristics of the firefly algorithm -- Chapter 7. Nature-inspired usability optimization -- Chapter 8. Evaluation of Bayesian network structure learning using elephant swarm water search -- Chapter 9. Multi-objective optimal power flow of integrated renewable systems using a novel evolutionary algorithm -- Chapter 10. Genetic algorithm-influenced top-n recommender system to alleviate the new user cold start problem -- Chapter 11. Experimental study on boundary constraints handling in particle swarm optimization -- Chapter 12. Contour gradient optimization -- Chapter 13. An analysis of fireworks algorithm solving problems with shifts in the decision space andobjective space -- Chapter 14. Population diversity of particle swarm optimization algorithm on solving single and multi-objective problems -- Chapter 15. A study of normalized population diversity in particle swarm optimization -- Chapter 16. Multi-objective short-term hydro-thermal scheduling using meta-heuristic approaches -- Chapter 17. Mobile anchor-assisted localization using invasive weed optimization algorithm. | |
506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
520 | 3 | |a "This book explores various concepts, principles, and applications of swarm intelligence algorithms"-- |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 04/22/2020). | ||
650 | 0 | |a Swarm intelligence. | |
700 | 1 | |a Cheng, Shi |d 1983- |e editor. | |
700 | 1 | |a Shi, Yuhui, |e editor. | |
710 | 2 | |a IGI Global, |e publisher. | |
776 | 0 | |c (Original) |w (DLC)2019049634 | |
776 | 0 | 8 | |i Print version: |z 1799832228 |z 9781799832225 |w (DLC) 2019049634 |
856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-3222-5 |3 Volltext |
912 | |a ZDB-98-IGB | ||
049 | |a DE-863 |
Datensatz im Suchindex
DE-BY-FWS_katkey | ZDB-98-IGB-00240813 |
---|---|
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adam_text | |
any_adam_object | |
author2 | Cheng, Shi 1983- Shi, Yuhui |
author2_role | edt edt |
author2_variant | s c sc y s ys |
author_facet | Cheng, Shi 1983- Shi, Yuhui |
building | Verbundindex |
bvnumber | localFWS |
callnumber-first | Q - Science |
callnumber-label | Q337 |
callnumber-raw | Q337.3 .H36 2020e |
callnumber-search | Q337.3 .H36 2020e |
callnumber-sort | Q 3337.3 H36 42020E |
callnumber-subject | Q - General Science |
collection | ZDB-98-IGB |
contents | Chapter 1. Newly-developed swarm intelligence algorithms applied to renewable energy-based load dispatch real-world problems -- Chapter 2. Semi-automatic sensor ontology matching based on interactive multi-objective evolutionary -- Chapter 3. A comparative study among recursive metaheuristics for gene selection -- Chapter 4. Training artificial neural networks with improved particle swarm optimization: case of electricity demand forecasting in Thailand -- Chapter 5. Segmentation and edge extraction of grayscale images using firefly and artificial bee colony agorithms -- Chapter 6. Analysis of the dynamic characteristics of the firefly algorithm -- Chapter 7. Nature-inspired usability optimization -- Chapter 8. Evaluation of Bayesian network structure learning using elephant swarm water search -- Chapter 9. Multi-objective optimal power flow of integrated renewable systems using a novel evolutionary algorithm -- Chapter 10. Genetic algorithm-influenced top-n recommender system to alleviate the new user cold start problem -- Chapter 11. Experimental study on boundary constraints handling in particle swarm optimization -- Chapter 12. Contour gradient optimization -- Chapter 13. An analysis of fireworks algorithm solving problems with shifts in the decision space andobjective space -- Chapter 14. Population diversity of particle swarm optimization algorithm on solving single and multi-objective problems -- Chapter 15. A study of normalized population diversity in particle swarm optimization -- Chapter 16. Multi-objective short-term hydro-thermal scheduling using meta-heuristic approaches -- Chapter 17. Mobile anchor-assisted localization using invasive weed optimization algorithm. |
ctrlnum | (CaBNVSL)slc00000445 (OCoLC)1128061785 |
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-00240813 |
illustrated | Not Illustrated |
indexdate | 2024-11-26T14:51:56Z |
institution | BVB |
isbn | 9781799832249 |
language | English |
oclc_num | 1128061785 |
open_access_boolean | |
owner | DE-863 DE-BY-FWS |
owner_facet | DE-863 DE-BY-FWS |
physical | 22 PDFs (482 pages) Also available in print. |
psigel | ZDB-98-IGB |
publishDate | 2020 |
publishDateSearch | 2020 |
publishDateSort | 2020 |
publisher | IGI Global, |
record_format | marc |
spelling | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems Shi Cheng and Yuhui Shi, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, [2020] 22 PDFs (482 pages) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Chapter 1. Newly-developed swarm intelligence algorithms applied to renewable energy-based load dispatch real-world problems -- Chapter 2. Semi-automatic sensor ontology matching based on interactive multi-objective evolutionary -- Chapter 3. A comparative study among recursive metaheuristics for gene selection -- Chapter 4. Training artificial neural networks with improved particle swarm optimization: case of electricity demand forecasting in Thailand -- Chapter 5. Segmentation and edge extraction of grayscale images using firefly and artificial bee colony agorithms -- Chapter 6. Analysis of the dynamic characteristics of the firefly algorithm -- Chapter 7. Nature-inspired usability optimization -- Chapter 8. Evaluation of Bayesian network structure learning using elephant swarm water search -- Chapter 9. Multi-objective optimal power flow of integrated renewable systems using a novel evolutionary algorithm -- Chapter 10. Genetic algorithm-influenced top-n recommender system to alleviate the new user cold start problem -- Chapter 11. Experimental study on boundary constraints handling in particle swarm optimization -- Chapter 12. Contour gradient optimization -- Chapter 13. An analysis of fireworks algorithm solving problems with shifts in the decision space andobjective space -- Chapter 14. Population diversity of particle swarm optimization algorithm on solving single and multi-objective problems -- Chapter 15. A study of normalized population diversity in particle swarm optimization -- Chapter 16. Multi-objective short-term hydro-thermal scheduling using meta-heuristic approaches -- Chapter 17. Mobile anchor-assisted localization using invasive weed optimization algorithm. Restricted to subscribers or individual electronic text purchasers. "This book explores various concepts, principles, and applications of swarm intelligence algorithms"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 04/22/2020). Swarm intelligence. Cheng, Shi 1983- editor. Shi, Yuhui, editor. IGI Global, publisher. (Original) (DLC)2019049634 Print version: 1799832228 9781799832225 (DLC) 2019049634 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-3222-5 Volltext |
spellingShingle | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems Chapter 1. Newly-developed swarm intelligence algorithms applied to renewable energy-based load dispatch real-world problems -- Chapter 2. Semi-automatic sensor ontology matching based on interactive multi-objective evolutionary -- Chapter 3. A comparative study among recursive metaheuristics for gene selection -- Chapter 4. Training artificial neural networks with improved particle swarm optimization: case of electricity demand forecasting in Thailand -- Chapter 5. Segmentation and edge extraction of grayscale images using firefly and artificial bee colony agorithms -- Chapter 6. Analysis of the dynamic characteristics of the firefly algorithm -- Chapter 7. Nature-inspired usability optimization -- Chapter 8. Evaluation of Bayesian network structure learning using elephant swarm water search -- Chapter 9. Multi-objective optimal power flow of integrated renewable systems using a novel evolutionary algorithm -- Chapter 10. Genetic algorithm-influenced top-n recommender system to alleviate the new user cold start problem -- Chapter 11. Experimental study on boundary constraints handling in particle swarm optimization -- Chapter 12. Contour gradient optimization -- Chapter 13. An analysis of fireworks algorithm solving problems with shifts in the decision space andobjective space -- Chapter 14. Population diversity of particle swarm optimization algorithm on solving single and multi-objective problems -- Chapter 15. A study of normalized population diversity in particle swarm optimization -- Chapter 16. Multi-objective short-term hydro-thermal scheduling using meta-heuristic approaches -- Chapter 17. Mobile anchor-assisted localization using invasive weed optimization algorithm. Swarm intelligence. |
title | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems |
title_auth | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems |
title_exact_search | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems |
title_full | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems Shi Cheng and Yuhui Shi, editors. |
title_fullStr | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems Shi Cheng and Yuhui Shi, editors. |
title_full_unstemmed | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems Shi Cheng and Yuhui Shi, editors. |
title_short | Handbook of research on advancements of swarm intelligence algorithms for solving real-world problems |
title_sort | handbook of research on advancements of swarm intelligence algorithms for solving real world problems |
topic | Swarm intelligence. |
topic_facet | Swarm intelligence. |
url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-3222-5 |
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