Elena Korchagina – författare

This book explores the transformative role of soft computing methods in increasing business analytics, providing a comprehensive look into how these advanced methods can be applied to complex business data for meaningful insights. Through the integration of neural network, fuzzy logic, genetic algorithms, artificial intelligence, machine learning, deep learning, and other innovative approaches, Intelligent Business Analytics: Harnessing the Power of Soft Computing for Data- Driven Insights presents a roadmap for leveraging computational intelligence in diverse areas of business decision- making.Readers will venture from predictive analytics and customer segmentation to real- time decision support systems and many other applications. Soft computing’s flexibility and applicability in the handling of uncertainty, ambiguity, and dynamic data environments shine throughout the book. Each chapter is created to be a base of theory and, at the same time, provide an applied example, so the book is appropriate for students, researchers, and professionals in the field.This book also discusses where the markets are heading and new applications that are in store for intelligent analytics to create a competitive advantage that also supports sustainable growth. At the end, this book is for those who want to learn more about using data-driven approaches and those who are ready to face the changes of the fast-evolving digital world.

Intelligent Business Analytics: Harnessing the Power of Soft Computing for Data-Driven Insights explores the transformative role of soft computing methods in improving business analytics. It looks at how intelligent analytical methods can be applied to complex business data to derive meaningful insight. It focuses on integrating such intelligent technologies as neural networks, fuzzy logic, genetic algorithms, AI, machine learning, and deep learning, to data analytics. The book examines:

Fundamental concepts of soft computing and its role in data analysis How neural networks and deep learning techniques can be used to analyze complex data patterns to make more accurate predictions Swarm intelligence techniques that can help identify hidden patterns in customer data and optimize marketing strategies Combining multiple soft computing techniques to create hybrid models for business recommendation systems Using machine learning techniques to analyze user behavior and brand interactions to provide personalized brand recommendations Advanced visualization techniques to interpret the complex results of soft computing models.

Other topics include predictive analytics, customer segmentation, real-time decision support systems, and soft computing to handle uncertainty, ambiguity, and dynamic data environments. Each chapter provides theory as well as an applied example, making the book a roadmap on how to leverage computational intelligence in diverse areas of business decision-making.