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Published by Springer, 2018
ISBN 10: 3319916408ISBN 13: 9783319916408
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: New.
Published by Springer, 2018
ISBN 10: 3319916408ISBN 13: 9783319916408
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: As New. Unread book in perfect condition.
Published by Springer International Publishing Mai 2018, 2018
ISBN 10: 3319916408ISBN 13: 9783319916408
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the thoroughly refereed revised selected papers of the 10 th International Conference on Bioinspired Optimization Models and Their Applications, BIOMA 2018, held in Paris, France, in May 2018.The 27 revised full papers were selected from 53 submissions and present papers in all aspects of bioinspired optimization research such as new algorithmic developments, high-impact applications, new research challenges, theoretical contributions, implementation issues, and experimental studies. 348 pp. Englisch.
Published by Springer, 2018
ISBN 10: 3319916408ISBN 13: 9783319916408
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Book
Condition: New.
Published by Springer International Publishing, 2018
ISBN 10: 3319916408ISBN 13: 9783319916408
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the thoroughly refereed revised selected papers of the 10 th International Conference on Bioinspired Optimization Models and Their Applications, BIOMA 2018, held in Paris, France, in May 2018.The 27 revised full papers were selected from 53 submissions and present papers in all aspects of bioinspired optimization research such as new algorithmic developments, high-impact applications, new research challenges, theoretical contributions, implementation issues, and experimental studies.
Published by Springer, 2018
ISBN 10: 3319916408ISBN 13: 9783319916408
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Book
Condition: New.
Published by Springer, 2022
ISBN 10: 3030969169ISBN 13: 9783030969165
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: New.
Published by Springer, 2019
ISBN 10: 3030187632ISBN 13: 9783030187637
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: New.
Published by Springer International Publishing, 2023
ISBN 10: 3030969193ISBN 13: 9783030969196
Seller: Buchpark, Trebbin, Germany
Book
Condition: Wie neu. Zustand: Wie neu | Seiten: 152 | Sprache: Englisch.
Published by Springer, 2019
ISBN 10: 3030187632ISBN 13: 9783030187637
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: As New. Unread book in perfect condition.
Published by Springer, 2022
ISBN 10: 3030969169ISBN 13: 9783030969165
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: As New. Unread book in perfect condition.
Published by Springer International Publishing Jun 2022, 2022
ISBN 10: 3030969169ISBN 13: 9783030969165
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Buch. Condition: Neu. 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.
Published by Springer International Publishing Jun 2023, 2023
ISBN 10: 3030969193ISBN 13: 9783030969196
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. 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.
Published by Springer International Publishing, 2022
ISBN 10: 3030969169ISBN 13: 9783030969165
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Published by Springer International Publishing, 2023
ISBN 10: 3030969193ISBN 13: 9783030969196
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.