Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems - Yeliz Karaca

Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems

Yeliz Karaca (Redaktør) ; Dumitru Baleanu (Redaktør) ; Yu-Dong Zhang (Redaktør) ; Osvaldo Gervasi (Redaktør) ; Majaz Moonis (Redaktør)

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. Les mer
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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.
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Utgitt:
Forlag: Academic Press Inc
Innbinding: Paperback
Språk: Engelsk
ISBN: 9780323900324
Format: 24 x 19 cm
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VURDERING
Gi vurdering
Les vurderinger
1. Introduction
Yeliz Karaca and Dumitru Baleanu
2. Theory of Complexity, Origin and Complex Systems
Yeliz Karaca
3. Multi-chaos, Fractal and Multi-fractional AI in Different Complex Systems
Yeliz Karaca
4. High Performance Computing and Computational Intelligence Applications with Multi-Chaos Perspective
Osvaldo Gervasi, Damiano Perri, Marco Simonetti, and Sergio Tasso
5. Human Hypercomplexity: Error and Unpredictability in Complex Multi-Chaotic Social Systems
Piero Dominici Sr.
6. Multifractal Complexity Analysis-based Dynamic Media Text Categorization Models by Natural Language Processing with BERT
Yeliz Karaca, Yu-Dong Zhang, Ahu Dereli Dursun, and Shui-Hua Wang
7. Mittag-Leffler Functions with Heavy-tailed Distributions’ Algorithm based on Different Biology Datasets to be Fit for Optimum Mathematical Models’ Strategies
Dumitru Baleanu and Yeliz Karaca
8. Artificial Neural Network Modeling of Systems Biology Datasets Fit Based on Mittag-Leffler Functions with Heavy-tailed Distributions for Diagnostic and Predictive Precision Medicine
Yeliz Karaca and Dumitru Baleanu
9. Computational Fractional-Order Calculus and Classical Calculus AI for Comparative Differentiability Prediction Analyses of Complex-systems-grounded Paradigm
Yeliz Karaca and Dumitru Baleanu
10. Pattern Formation Induced by Fractional-order Diffusive Model of COVID-19
Yeliz Karaca and Naveed Iqbal
11. Prony’s series in time and frequency domains and relevant fractional models
Jordan Hristov
12. A chain of kinetic equations of Bogoliubov-Born-Green-Kirkwood-Yvon and its application to non-equilibrium complex systems
Mukhayo Rasulova V, Tohir Vohidovich Akramov, Nicolai (Jr) Bogoliubov, and Umarbek Avazov
13. Hearing Loss Detection in Complex Setting by Stationary Wavelet Rényi Entropy and Three-Segment Biogeography-Based Optimization
Yabei Li, Junding Sun, and Chong Yao
14. Shannon Entropy-based Complexity Quantification of Nonlinear Stochastic Process: Diagnostic and Predictive Spatio-temporal Uncertainty of Multiple Sclerosis Subgroups
Yeliz Karaca, and Majaz Moonis
15. Chest X-ray image detection for pneumonia via complex convolutional neural network and Biogeography-based optimization
Junding Sun, Xiang Li, and Mengyao Zhai
16. Complex facial expression recognition via Densenet-121
Bin Li
17. Quantitative assessment of local warming based on urban dynamics using remote sensing techniques.
Valentina Santarsiero, Lucia Saganeiti, Angela Pilogallo, Francesco Scorza, Beniamino Murgante, Valentina Santarsiero, and Gabriele Nolè
18. Managing Information Security risk and Internet of Things (IoT) Impact on Challenges of Medicinal Problems with Complex Settings: A Complete Systematic Approach
N. Thirupathi Rao, Debnath Bhattacharyya, and Eali Stephen Neal Joshua
19. An Extensive Discussion on Utilization of Data Security and Big Data Models for Resolving Healthcare Problems
N. Thirupathi Rao, Debnath Bhattacharyya, and Eali Stephen Neal Joshua
Yeliz Karaca is an assistant professor of applied mathematics, and a researcher at the University of Massachusetts Medical School, USA. She received her Ph.D. degree in Mathematics from Marmara University, Istanbul, Turkey in 2012. Among the other awards, she was also granted the “Cooperation in Neurological Sciences and Support Award” by Turkish Neurology Association as the first mathematician in Turkey. Her research interests focus on computational methods, complex systems, computational complexity, nonlinear dynamics, fractals, multifractional methods with their applications, wavelets and entropy, advanced AI applications, solutions of advanced mathematical challenges, mathematical neuroscience and biology as well as advanced data analysis in medicine and other related domains. 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.