Computational Intelligence For Modern Business Systems

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Computational Intelligence for Modern Business Systems

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, architecture, brand identity, and product portfolio across the entire enterprise. The book will provide insights into research gaps, open challenges, and unsolved computational intelligence problems. The book will act as a premier reference and instant material for all the users who are contributing/practicing the adaptation of computational intelligence modern techniques in business systems.
Illustrated Computational Intelligence

Author: Priti Srinivas Sajja
language: en
Publisher: Springer Nature
Release Date: 2020-11-16
This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters. The remaining chapters of the book provide everything one must know about the basic artificial intelligence to modern machine intelligence techniques including the hybrid computational intelligence technique, using the concepts of several real-life solved examples, design of projects and research ideas. The solved examples with more than 200 illustrations presented in the book are a great help to instructors, students, non–AI professionals, and researchers. Each example is discussed in detail with encoding, normalization, architecture, detailed design, process flow, and sample input/output. Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book.
Applications of Artificial Intelligence in Business and Finance 5.0

This new book provides a valuable overview of how artificial intelligence (AI) applications are transforming global businesses and financial organizations, looking at the newest artificial intelligence-based solutions for e-commerce, corporate management, finance, banking and trading, and more. Chapters look at using AI and machine learning techniques to forecast and assess financial risks such as liquidity risk, volatility risk, and credit risk. The book also describes the use of natural language processing and text mining paired with machine learning models to assist in guiding sophisticated investors and corporate managers in financial decision making. Other topics include cryptocurrency in emerging markets; the role of artificial intelligence in making a positive impact on sustainable development; the use of fintech for micro, small and medium enterprises; the role of AI i financial education; the application of artificial intelligence in cyber security; and more.