Next-Generation Computational Intelligence: Trends and Technologies (eBook)

Artikelnummer: 978-3-031-96871-6
Einband: PDF
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Next-Generation Computational Intelligence: Trends and Technologies explores the transformative potential of advanced computational intelligence (CI) methods and their application across modern industries. With the rapid evolution of artificial intelligence, machine learning, and deep learning frameworks, this book provides a comprehensive overview of emerging CI trends and their role in shaping intelligent decision-making systems, automation, and data-driven innovation.

Contributors from academia and industry present cutting-edge research on neural networks, fuzzy systems, evolutionary algorithms, and hybrid intelligent systems, emphasizing real-world applications in domains such as healthcare, finance, smart manufacturing, cybersecurity, and intelligent transportation. The book also addresses challenges in scalability, interpretability, and sustainability, offering critical insights for researchers, practitioners, and policy-makers.

As part of the Information Systems Engineering and Management series, this volume serves as an essential resource for graduate students, researchers, engineers, and professionals seeking to harness the power of next-generation CI to drive digital transformation and competitive advantage.

Next-Generation Computational Intelligence: Trends and Technologies explores the transformative potential of advanced computational intelligence (CI) methods and their application across modern industries. With the rapid evolution of artificial intelligence, machine learning, and deep learning frameworks, this book provides a comprehensive overview of emerging CI trends and their role in shaping intelligent decision-making systems, automation, and data-driven innovation.

Contributors from academia and industry present cutting-edge research on neural networks, fuzzy systems, evolutionary algorithms, and hybrid intelligent systems, emphasizing real-world applications in domains such as healthcare, finance, smart manufacturing, cybersecurity, and intelligent transportation. The book also addresses challenges in scalability, interpretability, and sustainability, offering critical insights for researchers, practitioners, and policy-makers.

As part of the Information Systems Engineering and Management series, this volume serves as an essential resource for graduate students, researchers, engineers, and professionals seeking to harness the power of next-generation CI to drive digital transformation and competitive advantage.

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VerlagSpringer Nature Switzerland
EinbandPDF
Erscheinungsjahr2025
Seitenangabe413 S.
AusgabekennzeichenEnglisch
AbbildungenIX, 413 p. 123 illus., 112 illus. in color.
Masse15'965 KB
PlattformPDF
ReiheInformation Systems Engineering and Management; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorMahajan, Shubham (Hrsg.) / de Vasconcelos, José Braga (Hrsg.)

Alle Bände der Reihe "Information Systems Engineering and Management; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

Über den Autor Shubham (Hrsg.) Mahajan

Shubham Mahajan, PhD is a Post Doctoral Reseacher in the Department of Applied Data Science at Noroff Univeristy College in Kristiansand, Norway. He holds eleven Indian patents, one Australian and one German patent and has published more than 70 articles in peer-reviewed journals and conferences. His research interests span a wide array of topics, encompassing image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods, optimization, data mining, machine learning, robotics, and optical communication. Kamal Upreti, PhD is an Associate Professor in the Department of Computer Science at Christ University, Ghaziabad, India. He has published more than 50 patents, 32 magazine issues, 110 research papers in journals and international conferences, and 45 books. His areas of interest include modern physics, data analytics, cyber security, machine learning, healthcare, and embedded systems. Rashmi Agrawal, PhD is a Professor and Associate Dean at the School of Computer Applications at the Manav Rahna International Institute of Research and Studies, Faridabad, India with more than 23 years of experience. She has published more than 100 research papers in esteemed national and international journals and conferences and authored and co-authored books with distinguished publishers. Her research focuses on machine learning, classification, and pattern recognintion.

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