Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
Language: English
Published by Springer International Publishing Jun 2023, 2023
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 131.96
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Add to basketItem description from seller
This item is printed on demand - it takes 3-4 days longer - Neuware -Focusing oncomprehensive comparisonsof the performance of stochastic optimization algorithms, this book provides an overview of the current approachesused to analyzealgorithm performancein a range of commonscenarios, while also addressingissues that are often overlooked.In turn, itshows how these issues can be easily avoided by applyingtheprinciplesthat have producedDeep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective and multi-objective optimization data. At the end of the book, examplesfroma recently developed web-service-based e-learning tool(DSCTool) arepresented. The toolprovides users with all the functionalities needed to makerobust statistical comparison analysesinvariousstatistical scenarios.The book isintendedfornewcomers to the field and experienced researchers alike. For newcomers, it coversthe basicsofoptimization and statistical analysis,familiarizing themwith thesubject matterbefore introducingthe Deep Statistical Comparison approach. Experienced researcherscan quickly move on to the content on newstatistical approaches.The book is dividedinto three parts:Part I: Introduction to optimization, benchmarking, and statistical analysis - Chapters 2-4.Part II: Deep Statistical Comparison of meta-heuristic stochastic optimization algorithms - Chapters 5-7.Part III: Implementation and applicationof DeepStatistical Comparison - Chapter 8. 152 pp. Englisch.…
Seller Inventory # 9783030969196
- Title
- Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
- Author
- Peter Koro¿ec
- Publisher
- Springer International Publishing Jun 2023
- Publication year
- 2023
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030969193
- ISBN 13
- 9783030969196
- Item weight
- 242 grams
- Dimensions
- 235x155x9 mm
The book is intended for newcomers to the field and experienced researchers alike. For newcomers, it covers the basics of optimization and statistical analysis, familiarizing them with the subject matter before introducing the Deep Statistical Comparison approach. Experienced researchers can quickly move on to the content on new statistical approaches. The book is divided into three parts:
Part I: Introduction to optimization, benchmarking, and statistical analysis – Chapters 2-4.Part II: Deep Statistical Comparison of meta-heuristic stochastic optimization algorithms – Chapters 5-7.
Part III: Implementation and application of Deep Statistical Comparison – Chapter 8.
"Synopsis" may belong to another edition of this title.
About the Author
Tome Eftimov is currently a research fellow at the Jožef Stefan Institute, Ljubljana, Slovenia where he was awarded his PhD. He has since been a postdoctoral research fellow at the Dept. of Biomedical Data Science, and the Centre for Population Health Sciences, Stanford University, USA, and a research associate at the University of California, San Francisco, USA. His main areas of research include statistics, natural language processing, heuristic optimization, machine learning, and representational learning. His work related to benchmarking in computational intelligence is focused on developing more robust statistical approaches that can be used for the analysis of experimental data.
Peter Korošec received his PhD degree from the Jožef Stefan Postgraduate School, Ljubljana, Slovenia. Since 2002 he has been a researcher at the Computer Systems Department of the Jožef Stefan Institute, Ljubljana. He has participated in the organization of various conferencesworkshops as program chair or organizer. He has successfully applied his optimization approaches to several real-world problems in engineering. Recently, he has focused on better understanding optimization algorithms so that they can be more efficiently selected and applied to real-world problems.
The authors have presented the related tutorial at the significant related international conferences in Evolutionary Computing, including GECCO, PPSN, and SSCI.
"About the title" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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