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"--
Saved in:
| Other Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
[2020]
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "This book explores various concepts, principles, and applications of swarm intelligence algorithms"-- |
| Physical Description: | 22 PDFs (482 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781799832249 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
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| 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 Seiten) | ||
| 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 | 0 | |a Description based on title screen (IGI Global, viewed 04/22/2020). | |
| 650 | 0 | |a Swarm intelligence. | |
| 653 | |a Bio-Inspired Computing. | ||
| 653 | |a Computational Intelligence. | ||
| 653 | |a Evolutionary Programming. | ||
| 653 | |a Fuzzy Systems. | ||
| 653 | |a Genetic Algorithms. | ||
| 653 | |a Machine Learning. | ||
| 653 | |a Multi-Agent Systems. | ||
| 653 | |a Optimization. | ||
| 653 | |a Swarm Robotics. | ||
| 653 | |a Virtual Reality. | ||
| 700 | 1 | |a Cheng, Shi |d 1983- |e editor. | |
| 700 | 1 | |a Shi, Yuhui |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
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Record in the Search Index
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|---|---|
| _version_ | 1826942598089015296 |
| 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 |
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| 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 |
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| 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 | 2025-03-18T14:30:33Z |
| institution | BVB |
| isbn | 9781799832249 |
| language | English |
| oclc_num | 1128061785 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 22 PDFs (482 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB 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 Seiten) 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. Bio-Inspired Computing. Computational Intelligence. Evolutionary Programming. Fuzzy Systems. Genetic Algorithms. Machine Learning. Multi-Agent Systems. Optimization. Swarm Robotics. Virtual Reality. Cheng, Shi 1983- editor. Shi, Yuhui editor. IGI Global, publisher. (Original) (DLC)2019049634 Print version: 1799832228 9781799832225 (DLC) 2019049634 |
| 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. |
| work_keys_str_mv | AT chengshi handbookofresearchonadvancementsofswarmintelligencealgorithmsforsolvingrealworldproblems AT shiyuhui handbookofresearchonadvancementsofswarmintelligencealgorithmsforsolvingrealworldproblems AT igiglobal handbookofresearchonadvancementsofswarmintelligencealgorithmsforsolvingrealworldproblems |