Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems
Language: English
Published by Elsevier Inc Jun 2022, 2022
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Neuware - Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems addresses different uncertain processes inherent in the complex systems, attempting to provide global and robust optimized solutions distinctively through multifarious methods, technical analyses, modeling, optimization processes, numerical simulations, case studies as well as applications including theoretical aspects of complexity. Foregrounding Multi-chaos, Fractal and Multi-fractional in the era of Artificial Intelligence (AI), the edited book deals with multi- chaos, fractal, multifractional, fractional calculus, fractional operators, quantum, wavelet, entropy-based applications, artificial intelligence, mathematics-informed and data driven processes aside from the means of modelling, and simulations for the solution of multifaceted problems characterized by nonlinearity, non-regularity and self-similarity, frequently encountered in different complex systems. The fundamental interacting components underlying complexity, complexity thinking, processes and theory along with computational processes and technologies, with machine learning as the core component of AI demonstrate the enabling of complex data to augment some critical human skills. Appealing to an interdisciplinary network of scientists and researchers to disseminate the theory and application in medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, social sciences and other far-reaching domains, the overarching aim is to empower out-of-the-box thinking through multifarious methods, directed towards paradoxical situations, uncertain processes, chaotic, transient and nonlinear dynamics of complex systems.…
Seller Inventory # 9780323900324
- Title
- Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems
- Author
- Yeli Karaca
- Publisher
- Elsevier Inc Jun 2022
- Publication year
- 2022
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0323900321
- ISBN 13
- 9780323900324
- Item weight
- 818 grams
- Dimensions
- 279x216x19 mm
Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems addresses different uncertain processes inherent in the complex systems, attempting to provide global and robust optimized solutions distinctively through multifarious methods, technical analyses, modeling, optimization processes, numerical simulations, case studies as well as applications including theoretical aspects of complexity. Foregrounding Multi-chaos, Fractal and Multi-fractional in the era of Artificial Intelligence (AI), the edited book deals with multi- chaos, fractal, multifractional, fractional calculus, fractional operators, quantum, wavelet, entropy-based applications, artificial intelligence, mathematics-informed and data driven processes aside from the means of modelling, and simulations for the solution of multifaceted problems characterized by nonlinearity, non-regularity and self-similarity, frequently encountered in different complex systems. The fundamental interacting components underlying complexity, complexity thinking, processes and theory along with computational processes and technologies, with machine learning as the core component of AI demonstrate the enabling of complex data to augment some critical human skills. Appealing to an interdisciplinary network of scientists and researchers to disseminate the theory and application in medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, social sciences and other far-reaching domains, the overarching aim is to empower out-of-the-box thinking through multifarious methods, directed towards paradoxical situations, uncertain processes, chaotic, transient and nonlinear dynamics of complex systems.
- Constructs and presents a multifarious approach for critical decision-making processes embodying paradoxes and uncertainty.
- Includes a combination of theory and applications with regard to multi-chaos, fractal and multi-fractional as well as AI of different complex systems and many-body systems.
- Provides readers with a bridge between application of advanced computational mathematical methods and AI based on comprehensive analyses and broad theories.
"Synopsis" may belong to another edition of this title.
About the Author
Yeliz Karaca is an Assistant Professor of Applied Mathematics, and a researcher at the University of Massachusetts (UMass) Chan Medical School, Worcester, USA. She received her Ph.D. degree in Mathematics in 2012. Along with the other awards she has been conferred, she was granted the Cooperation in Neurological Sciences and Support Award by Turkish Neurology Association as the first mathematician in Turkey. She also holds a medical card as the only mathematician entitled for it. Furthermore, she received the Outstanding Young Scientist Award in 2012 and Best Paper Awards in her specialized discipline, among the other national and international awards in different categories as well as grants. Another award of hers is Outstanding Reviewer Award (Mathematics Journal, MDPI) in 2021. She is the Editor-in-Chief of the book series named Systems Science & Nonlinear Intelligence Dynamics by World Scientific. Dr. Karaca has been acting as the lead editor, editor and associate editor in many different SCI indexed journals. She also has active involvement with diverse projects, some of which are Institute of Electrical and Electronics Engineers (IEEE, as senior member), Organization for Women in Science for the Developing World (OWSD); Complex Human Adaptive Organizations and Systems (CHAOS)- University of Perugia, Italy; International Engineering and Technology Institute (IETI, as the member of Board of Director). Her research interests include complex systems sciences with applications in various terrains, applied mathematics, advanced computational methods, AI applications, computational complexity, fractional calculus, fractals and multifractals, stochastic processes, different kinds of differential and difference equations, discrete mathematics, algebraic complexity, complexity science, wavelet and entropy, solutions of advanced mathematical challenges, mathematical neuroscience and biology as well as advanced data analysis in medicine and other related theoretical, computational and applied domains.
Affiliations and expertise
Assistant Professor of Applied Mathematics and Researcher, University of Massachusetts (UMass) Medical School, Worcester, Massachusetts, USA
Dumitru Baleanu is a professor at the Institute of Space Sciences, Magurele-Bucharest, Romania and a visiting staff member at the Department of Mathematics, Çankaya, University, Ankara, Turkey. He received his Ph.D. from the Institute of Atomic Physics in 1996. His fields of interest include Fractional Dynamics and its applications, Fractional Differential Equations and their applications, Discrete Mathematics, Image Processing, Bioinformatics, Mathematical Biology, Mathematical Physics, Soliton Theory, Lie Symmetry, Dynamic Systems on time scales, Computational Complexity, the Wavelet Method and its applications, Quantization of systems with constraints, the Hamilton-Jacobi Formalism, as well as geometries admitting generic and non-generic symmetries.
Yu-Dong Zhang received his Ph.D. from Southeast University. He worked as postdoc from 2010 to 2012 in Columbia University, USA, and as an assistant research scientist from 2012 to 2013 at the Research Foundation of Mental Hygiene, USA. He served as a full professor from 2013 to 2017 in Nanjing Normal University, where he was the founding director of Advanced Medical Image Processing Group in NJNU. He currently works as a professor in the Department of Informatics, University of Leicester, UK. His research interests include deep learning, convolutional neural networks, graph convolutional networks, attention networks, explainable AI, medical image analysis, bio-inspired computing, pattern recognition, transfer learning and medical sensors.
Osvaldo Gervasi is a professor at the Department of Mathematics and Computer Science in Perugia University, temporarily serving as deputy director. His scientific interests focus on parallel and distributed systems, computational science, virtual and augmented reality, artificial intelligence, free and libre open source software. He has served as the General Co-Chair or Program Co-Chair of the International Conference on Computational Science and Its Applications (ICCSA) since 2004 and is the President of the not for profit organization ICCSA.
Majaz Moonis is a professor of Neurology and Psychiatry and Director of Stroke Services and Vascular Neurology Program in the University of Massachusetts Medical School and affiliated UMass Memorial Medical Center. His fields of interests include stroke outcomes, particularly role of statins and other medications on the vascular endothelium and its impact in improving stroke and dementia outcomes, automatic detection of AF for a wristwatch (CoPI), and interactions between stroke and dementia with emphasis on machine learning algorithms. He is also involved in clinical and medical applications to provide solutions to challenging health concerns.
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