Unlocking Complex Systems: Multi-Chaos, Fractal, and Multi-Fractional Artificial Intelligence

Authored by Yeliz Karaca, this comprehensive book delves into the intricate world of complex systems, tackling the uncertain processes that govern them. By leveraging multifaceted approaches, technical analyses, modeling, optimization processes, numerical simulations, and case studies, the book provides global and robust solutions to these complex problems.

Embracing the Era of Artificial Intelligence

In the realm of Artificial Intelligence (AI), this edited book shines a spotlight on multi-chaos, fractal, and multi-fractional aspects, exploring their applications in theoretical and practical contexts. The book covers a wide range of topics, including fractional calculus, fractional operators, quantum, wavelet, and entropy-based applications, as well as mathematics-informed and data-driven processes.

By harnessing the power of machine learning, a core component of AI, the book demonstrates how complex data can augment critical human skills. This interdisciplinary approach appeals to scientists and researchers across diverse domains, including medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, and social sciences.

A Multifarious Approach to Critical Decision-Making

This book presents a unique approach to critical decision-making, incorporating paradoxes and uncertainty into the equation. By combining theory and application, it provides readers with a comprehensive understanding of multi-chaos, fractal, and multi-fractional AI in complex systems and many-body systems.

By bridging the gap between advanced computational mathematical methods and AI, this book offers a valuable resource for readers seeking to navigate the complexities of real-world problems. The book’s overarching aim is to empower out-of-the-box thinking, enabling readers to tackle paradoxical situations, uncertain processes, and nonlinear dynamics in complex systems.

Product Details:

Published by Elsevier Science on June 22, 2022

Language: English

ISBN: 9780323900324, 9780323886161