Computational Intelligence Applications in Business Intelligence and Big Data Analytics

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intell

Format: Paperback / softback
Length: 378 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

Computational intelligence (CI) is a rapidly evolving field that encompasses a wide range of paradigms and algorithms. While there are numerous books on CI, they often provide a broad overview of CI concepts rather than delve into the intricacies of learning and adaptive mechanisms. This book, however, takes a different approach by focusing on computational intelligence-based architectures, modeling, case studies, and applications in big data analytics and business intelligence.

The primary target audience of this book includes scientists, professionals, researchers, and academicians who are actively engaged in addressing the emerging challenges and advancements in these specific areas. By reading this book, designers and developers of applications in these domains can gain valuable insights and expertise from other experts and colleagues in the field.

In the first chapter, the book provides an introduction to computational intelligence and its various applications. It discusses the importance of CI in solving complex problems and highlights the key challenges that arise in different domains. The chapter also introduces the basic concepts and principles of CI, including neural networks, machine learning, and genetic algorithms.

Chapter 2 delves into computational intelligence-based architectures and their role in solving complex problems. It discusses the different types of CI architectures, such as artificial neural networks, fuzzy systems, and evolutionary algorithms, and their advantages and disadvantages. The chapter also provides examples of real-world applications of CI-based architectures in fields such as image processing, speech recognition, and natural language processing.

Chapter 3 explores computational intelligence modeling and its applications in big data analytics. It discusses the challenges of analyzing large datasets and the importance of developing efficient modeling techniques. The chapter introduces various modeling techniques, such as regression analysis, decision trees, and neural networks, and their applications in predicting customer behavior, identifying fraudulent transactions, and analyzing medical data.

Chapter 4 focuses on case studies and applications of computational intelligence in business intelligence. It discusses the use of CI in decision-making processes, such as customer segmentation, supply chain optimization, and risk assessment. The chapter provides examples of real-world applications of CI in various industries, such as finance, healthcare, and retail.

Chapter 5 concludes the book by discussing the future trends and challenges in computational intelligence. It discusses the potential applications of CI in emerging fields such as autonomous vehicles, healthcare, and artificial intelligence. The chapter also highlights the need for interdisciplinary collaboration and the development of new research methodologies to address the complex challenges of CI.

In conclusion, this book provides a comprehensive and in-depth exploration of computational intelligence-based architectures, modeling, case studies, and applications in big data analytics and business intelligence. It is an invaluable resource for scientists, professionals, researchers, and academicians who are interested in advancing their knowledge and expertise in these fields. By reading this book, designers and developers of applications in these domains can gain valuable insights and expertise from other experts and colleagues in the field.

Weight: 700g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032476766