| 書目名稱 | Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms |
| 編輯 | Tome Eftimov,Peter Koro?ec |
| 視頻video | http://file.papertrans.cn/265/264674/264674.mp4 |
| 概述 | Presents a comprehensive comparison of the performance of stochastic optimization algorithms.Includes an introduction to benchmarking and statistical analysis.Provides a web-based tool for making stat |
| 叢書名稱 | Natural Computing Series |
| 圖書封面 |  |
| 描述 | Focusing on?comprehensive comparisons?of the performance of stochastic optimization algorithms, this book provides an overview of the current approaches?used to analyze?algorithm performance?in a range of common?scenarios, while also addressing?issues that are often overlooked.?In turn, it?shows how these issues can be easily avoided by applying?the?principles?that have produced?Deep 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, examples?from?a recently developed web-service-based e-learning tool?(DSCTool) are?presented. The tool?provides users with all the functionalities needed to make?robust statistical comparison analyses?in?various?statistical scenarios..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: Int |
| 出版日期 | Book 2022 |
| 關(guān)鍵詞 | Metaheuristics; Stochastic Optimization; Optimization; Benchmarking; Statistical Analysis; Multiobjective |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-96917-2 |
| isbn_softcover | 978-3-030-96919-6 |
| isbn_ebook | 978-3-030-96917-2Series ISSN 1619-7127 Series E-ISSN 2627-6461 |
| issn_series | 1619-7127 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機版|小黑屋|
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