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Artificial Intelligence, Optimization, and Data Sciences in Sports / edited by Maude J. Blondin, Iztok Fister Jr., Panos M. Pardalos

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Springer Optimization and Its Applications ; 218Publisher: Cham : Springer Nature Switzerland, 2025Publisher: Cham : Imprint: Springer, 2025Edition: 1st ed. 2025Description: 1 Online-Ressource(XI, 353 p. 60 illus., 50 illus. in color.)ISBN:
  • 9783031760471
Subject(s): Additional physical formats: 9783031760464 | 9783031760488 | 9783031760495 | Erscheint auch als: 9783031760464 Druck-Ausgabe | Erscheint auch als: 9783031760488 Druck-Ausgabe | Erscheint auch als: 9783031760495 Druck-Ausgabe | Erscheint auch als: Artificial intelligence, optimization, and data sciences in sports. Druck-Ausgabe. Cham, Switzerland : Springer Nature, 2025. xi, 353 SeitenDDC classification:
  • 519.6 23
DOI: DOI: 10.1007/978-3-031-76047-1Online resources: Summary: Chapter 1. Artificial Intelligence, Optimization, and Data Sciences in Sports: Editorial -- Chapter 2. Machine Learning for Soccer Match Result Prediction -- Chapter 3. Machine learning for prediction of the index of effec-tiveness in cycling -- Chapter 4. Machine Learning in Biomechanics: Key Applications and Limitations in Walking, Running, and Sports Movements -- Chapter 5. Artificial Intelligence & Machine Learning-Based Data Analytics for Sports. General Overview & NBA Case Study -- Chapter 6. An ecological dynamics approach to the use of Artificial Intelligence and Machine Learning to analyse performance in football -- Chapter 7. A Supervised Learning Approach for Evaluating Football Performances -- Chapter 8. Bridging Route based Cycling Training with Digital Twins -- Chapter 9. Perspectives of Artificial Intelligence in Training and Exercise -- Chapter 10. A fuzzy model for optimise the football rule assuring spectacle, fair play, objectivity and ethics -- Chapter 11. Physical Efficiency in Soccer: Relevance, Correlations and Impacts using AI Methods -- Chapter 12. A PageRank-Based Method for College Football Recruiting Rankings -- Chapter 13. APPLICATIONS OF IMPROVEMENTS TO THE PYTHAGOREAN WON-LOST EXPECTATION IN OPTIMIZING ROSTERS.Summary: This book delves into the dynamic intersection of data science, data mining, machine learning, and optimization within sports. It compiles and presents the latest achievements in this vibrant and emerging research area, offering a comprehensive overview of how these technologies revolutionize sports analytics and performance. Topical coverage includes artificial intelligence in sports, automated machine learning for training sessions, computational social science, and deep learning applications. Readers will also explore cutting-edge concepts such as digital twins in sports and sports prediction through data analysis. This volume highlights theoretical advancements and practical case studies that demonstrate real-world applications. Ideal for researchers, practitioners, and students in fields related to sports science, data analytics, and machine learning, this book serves as a crucial resource for anyone looking to understand the transformative impact of technology on sports. Whether you are an academic scholar or a professional working in the industry, this collection offers valuable insights that bridge the gap between research and practical solutions.PPN: PPN: 1916312691Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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