Kniha Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms Tome Eftimov

Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

Jazyk: Angličtina
Vazba: Pevná
Vydavatel: Springer, Berlin
Dostupnost: Skladem u dodavatele
Odesíláme za 10-13 dnů
3 198
This book will provide an overview of the current approaches for analyzing algorithm performance in...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Pevná
Vydáno
2022
Stránek
133
EAN
9783030969165
Enbook ID
38627491
Vydavatel
Hmotnost
401
Rozměry
155 x 12 x 14

Kompletní popis

This book will provide an overview of the current approaches for analyzing algorithm performance in different commonly used scenarios by emphasizing issues that are often overlooked. The book will also show how these issues can be easily avoided by applying principles that lead to Deep Statistical Comparison and its variants. The focus will be on statistical analyses performed using single-objective and multiobjective optimization data. At the end of the book, examples of a recently developed web-service-based e-learning tool, known as DSCTool, will be presented. The tool provides the users with all the required functionalities in order to make a proper robust statistical comparison analysis in different statistical scenarios.The authors have presented the related tutorial at the significant related international conferences in Evolutionary Computing, including GECCO, PPSN, and SSCI, and the book is approved for publication in our Natural Computing book series.

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