Computational Intelligence in Sports
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First International Conference, ICAIDS 2021, Hyderabad, India, December 17–18, 2021, Revised Selected Papers
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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.
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This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.
This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.
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