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Titlebook: Computational Intelligence for Modern Business Systems; Emerging Application Sandeep Kautish,Prasenjit Chatterjee,Deepmala Sing Book 2024 T

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书目名称Computational Intelligence for Modern Business Systems
副标题Emerging Application
编辑Sandeep Kautish,Prasenjit Chatterjee,Deepmala Sing
视频videohttp://file.papertrans.cn/233/232454/232454.mp4
概述Serves as a strong technological convergence solution for industry professionals, academicians, and researchers.Includes information on the integrated platform of business applications and computation
丛书名称Disruptive Technologies and Digital Transformations for Society 5.0
图书封面Titlebook: Computational Intelligence for Modern Business Systems; Emerging Application Sandeep Kautish,Prasenjit Chatterjee,Deepmala Sing Book 2024 T
描述.This book covers the applications of computational intelligence techniques in business systems and advocates how these techniques are useful in modern business operations. The book redefines the computational intelligence foundations, the three pillars - neural networks, evolutionary computation, and fuzzy systems. It also discusses emerging areas such as swarm intelligence, artificial immune systems (AIS), support vector machines, rough sets, and chaotic systems. The other areas have also been demystified in the book to strengthen the range of computational intelligence techniques such as expert systems, knowledge-based systems, and genetic algorithms. Therefore, this book will redefine the role of computational intelligence techniques in modern business system operations such as marketing, finance & accounts, operations, personnel management, supply chain management, and logistics. Besides, this book guides the readers through using them to model, discover, and interpret new patterns that cannot be found through statistical methods alone in various business system operations. This book reveals how computational intelligence can inform the design and integration of services, arch
出版日期Book 2024
关键词Computational Intelligence; Business Intelligence; Predictive Models; Customer Analytics; Business Analy
版次1
doihttps://doi.org/10.1007/978-981-99-5354-7
isbn_softcover978-981-99-5356-1
isbn_ebook978-981-99-5354-7Series ISSN 2730-9061 Series E-ISSN 2730-907X
issn_series 2730-9061
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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