Handbook of research on fireworks algorithms and swarm intelligence:
""This book provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniq...
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 provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm"--Provided by publisher"-- |
| Beschreibung: | 31 PDFs (471 pages) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781799816607 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
| LEADER | 00000nam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-98-IGB-00233811 | ||
| 003 | IGIG | ||
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| 024 | 7 | |a 10.4018/978-1-7998-1659-1 |2 doi | |
| 035 | |a (CaBNVSL)slc00000387 | ||
| 035 | |a (OCoLC)1151202629 | ||
| 040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
| 050 | 4 | |a TP300 |b .H36 2020e | |
| 082 | 7 | |a 662/.1 |2 23 | |
| 245 | 0 | 0 | |a Handbook of research on fireworks algorithms and swarm intelligence |c Ying Tan, editor. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c 2020. | |
| 300 | |a 31 PDFs (471 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. Survey of FWA studies and applications. Chapter 1. Recent developments of fireworks algorithms -- Section 2. Algorithm improvements on FWA. Chapter 2. Last-position elimination-based fireworks algorithm for function optimization ; Chapter 3. Explosion operation of fireworks algorithm -- Section 3. FWA applications in machine learning. Chapter 4. EFWA as a method of optimizing model parameters: example of an expensive function evaluation ; Chapter 5. Learning from class imbalance: a fireworks-based resampling for weighted pattern matching classifier (PMC) ; Chapter 6. An improved dynamic search fireworks algorithm optimizes extreme learning machine to predict virtual machine fault ; Chapter 7. A classification model based on improved self-adaptive fireworks algorithm ; Chapter 8. Development and performance analysis of fireworks algorithm-trained artificial neural network (FWANN): a case study on financial time series forecasting ; Chapter 9. Interval type 2 fuzzy fireworks algorithm for clustering -- Section 4. FWA application in engineering. Chapter 10. A hybrid fireworks algorithm to navigation and mapping ; Chapter 11. Application of fireworks algorithm in bioinformatics ; Chapter 12. Increasing energy efficiency by optimizing the electrical infrastructure of a railway Line using fireworks algorithm ; Chapter 13. Hybrid bare bones fireworks algorithm for load flow analysis of islanded microgrids ; Chapter 14. A fireworks-based approach for efficient packet filtering in firewall ; Chapter 15. Innovative aspects of virtual reality and kinetic sensors for significant improvement using fireworks algorithm in a wii game of a collaborative sport -- Section 5. Innovative applications of swarm intelligence and swarm robotics. Chapter 16. Optimization of PID controller for a hybrid power system using particle swarm optimization technique ; Chapter 17. A survey on the applications of swarm intelligence to software verification ; Chapter 18. Research on the construction of underwater platform combat deduction system based on service-oriented and multi-agent technology. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a ""This book provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm"--Provided by publisher"-- |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 04/15/2020). | ||
| 650 | 0 | |a Fireworks |x Research. | |
| 650 | 0 | |a Swarm intelligence. | |
| 650 | 7 | |a Swarm intelligence. |2 fast | |
| 700 | 1 | |a Tan, Ying |d 1964- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | |c (Original) |w (DLC)2019032849 | |
| 776 | 0 | 8 | |i Print version: |z 1799816591 |z 9781799816591 |w (DLC) 2019032849 |
| 856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-1659-1 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00233811 |
|---|---|
| _version_ | 1816797082742161408 |
| adam_text | |
| any_adam_object | |
| author2 | Tan, Ying 1964- |
| author2_role | edt |
| author2_variant | y t yt |
| author_facet | Tan, Ying 1964- |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | T - Technology |
| callnumber-label | TP300 |
| callnumber-raw | TP300 .H36 2020e |
| callnumber-search | TP300 .H36 2020e |
| callnumber-sort | TP 3300 H36 42020E |
| callnumber-subject | TP - Chemical Technology |
| collection | ZDB-98-IGB |
| contents | Section 1. Survey of FWA studies and applications. Chapter 1. Recent developments of fireworks algorithms -- Section 2. Algorithm improvements on FWA. Chapter 2. Last-position elimination-based fireworks algorithm for function optimization ; Chapter 3. Explosion operation of fireworks algorithm -- Section 3. FWA applications in machine learning. Chapter 4. EFWA as a method of optimizing model parameters: example of an expensive function evaluation ; Chapter 5. Learning from class imbalance: a fireworks-based resampling for weighted pattern matching classifier (PMC) ; Chapter 6. An improved dynamic search fireworks algorithm optimizes extreme learning machine to predict virtual machine fault ; Chapter 7. A classification model based on improved self-adaptive fireworks algorithm ; Chapter 8. Development and performance analysis of fireworks algorithm-trained artificial neural network (FWANN): a case study on financial time series forecasting ; Chapter 9. Interval type 2 fuzzy fireworks algorithm for clustering -- Section 4. FWA application in engineering. Chapter 10. A hybrid fireworks algorithm to navigation and mapping ; Chapter 11. Application of fireworks algorithm in bioinformatics ; Chapter 12. Increasing energy efficiency by optimizing the electrical infrastructure of a railway Line using fireworks algorithm ; Chapter 13. Hybrid bare bones fireworks algorithm for load flow analysis of islanded microgrids ; Chapter 14. A fireworks-based approach for efficient packet filtering in firewall ; Chapter 15. Innovative aspects of virtual reality and kinetic sensors for significant improvement using fireworks algorithm in a wii game of a collaborative sport -- Section 5. Innovative applications of swarm intelligence and swarm robotics. Chapter 16. Optimization of PID controller for a hybrid power system using particle swarm optimization technique ; Chapter 17. A survey on the applications of swarm intelligence to software verification ; Chapter 18. Research on the construction of underwater platform combat deduction system based on service-oriented and multi-agent technology. |
| ctrlnum | (CaBNVSL)slc00000387 (OCoLC)1151202629 |
| dewey-full | 662/.1 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 662 - Explosives, fuels & related products |
| dewey-raw | 662/.1 |
| dewey-search | 662/.1 |
| dewey-sort | 3662 11 |
| dewey-tens | 660 - Chemical engineering |
| discipline | Chemie / Pharmazie |
| format | Electronic eBook |
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| id | ZDB-98-IGB-00233811 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:51:55Z |
| institution | BVB |
| isbn | 9781799816607 |
| language | English |
| oclc_num | 1151202629 |
| open_access_boolean | |
| owner | DE-863 DE-BY-FWS |
| owner_facet | DE-863 DE-BY-FWS |
| physical | 31 PDFs (471 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 fireworks algorithms and swarm intelligence Ying Tan, editor. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, 2020. 31 PDFs (471 pages) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Section 1. Survey of FWA studies and applications. Chapter 1. Recent developments of fireworks algorithms -- Section 2. Algorithm improvements on FWA. Chapter 2. Last-position elimination-based fireworks algorithm for function optimization ; Chapter 3. Explosion operation of fireworks algorithm -- Section 3. FWA applications in machine learning. Chapter 4. EFWA as a method of optimizing model parameters: example of an expensive function evaluation ; Chapter 5. Learning from class imbalance: a fireworks-based resampling for weighted pattern matching classifier (PMC) ; Chapter 6. An improved dynamic search fireworks algorithm optimizes extreme learning machine to predict virtual machine fault ; Chapter 7. A classification model based on improved self-adaptive fireworks algorithm ; Chapter 8. Development and performance analysis of fireworks algorithm-trained artificial neural network (FWANN): a case study on financial time series forecasting ; Chapter 9. Interval type 2 fuzzy fireworks algorithm for clustering -- Section 4. FWA application in engineering. Chapter 10. A hybrid fireworks algorithm to navigation and mapping ; Chapter 11. Application of fireworks algorithm in bioinformatics ; Chapter 12. Increasing energy efficiency by optimizing the electrical infrastructure of a railway Line using fireworks algorithm ; Chapter 13. Hybrid bare bones fireworks algorithm for load flow analysis of islanded microgrids ; Chapter 14. A fireworks-based approach for efficient packet filtering in firewall ; Chapter 15. Innovative aspects of virtual reality and kinetic sensors for significant improvement using fireworks algorithm in a wii game of a collaborative sport -- Section 5. Innovative applications of swarm intelligence and swarm robotics. Chapter 16. Optimization of PID controller for a hybrid power system using particle swarm optimization technique ; Chapter 17. A survey on the applications of swarm intelligence to software verification ; Chapter 18. Research on the construction of underwater platform combat deduction system based on service-oriented and multi-agent technology. Restricted to subscribers or individual electronic text purchasers. ""This book provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm"--Provided by publisher"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 04/15/2020). Fireworks Research. Swarm intelligence. Swarm intelligence. fast Tan, Ying 1964- editor. IGI Global, publisher. (Original) (DLC)2019032849 Print version: 1799816591 9781799816591 (DLC) 2019032849 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-1659-1 Volltext |
| spellingShingle | Handbook of research on fireworks algorithms and swarm intelligence Section 1. Survey of FWA studies and applications. Chapter 1. Recent developments of fireworks algorithms -- Section 2. Algorithm improvements on FWA. Chapter 2. Last-position elimination-based fireworks algorithm for function optimization ; Chapter 3. Explosion operation of fireworks algorithm -- Section 3. FWA applications in machine learning. Chapter 4. EFWA as a method of optimizing model parameters: example of an expensive function evaluation ; Chapter 5. Learning from class imbalance: a fireworks-based resampling for weighted pattern matching classifier (PMC) ; Chapter 6. An improved dynamic search fireworks algorithm optimizes extreme learning machine to predict virtual machine fault ; Chapter 7. A classification model based on improved self-adaptive fireworks algorithm ; Chapter 8. Development and performance analysis of fireworks algorithm-trained artificial neural network (FWANN): a case study on financial time series forecasting ; Chapter 9. Interval type 2 fuzzy fireworks algorithm for clustering -- Section 4. FWA application in engineering. Chapter 10. A hybrid fireworks algorithm to navigation and mapping ; Chapter 11. Application of fireworks algorithm in bioinformatics ; Chapter 12. Increasing energy efficiency by optimizing the electrical infrastructure of a railway Line using fireworks algorithm ; Chapter 13. Hybrid bare bones fireworks algorithm for load flow analysis of islanded microgrids ; Chapter 14. A fireworks-based approach for efficient packet filtering in firewall ; Chapter 15. Innovative aspects of virtual reality and kinetic sensors for significant improvement using fireworks algorithm in a wii game of a collaborative sport -- Section 5. Innovative applications of swarm intelligence and swarm robotics. Chapter 16. Optimization of PID controller for a hybrid power system using particle swarm optimization technique ; Chapter 17. A survey on the applications of swarm intelligence to software verification ; Chapter 18. Research on the construction of underwater platform combat deduction system based on service-oriented and multi-agent technology. Fireworks Research. Swarm intelligence. Swarm intelligence. fast |
| title | Handbook of research on fireworks algorithms and swarm intelligence |
| title_auth | Handbook of research on fireworks algorithms and swarm intelligence |
| title_exact_search | Handbook of research on fireworks algorithms and swarm intelligence |
| title_full | Handbook of research on fireworks algorithms and swarm intelligence Ying Tan, editor. |
| title_fullStr | Handbook of research on fireworks algorithms and swarm intelligence Ying Tan, editor. |
| title_full_unstemmed | Handbook of research on fireworks algorithms and swarm intelligence Ying Tan, editor. |
| title_short | Handbook of research on fireworks algorithms and swarm intelligence |
| title_sort | handbook of research on fireworks algorithms and swarm intelligence |
| topic | Fireworks Research. Swarm intelligence. Swarm intelligence. fast |
| topic_facet | Fireworks Research. Swarm intelligence. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-1659-1 |
| work_keys_str_mv | AT tanying handbookofresearchonfireworksalgorithmsandswarmintelligence AT igiglobal handbookofresearchonfireworksalgorithmsandswarmintelligence |