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.
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Techn.
Dateigröße
ISBN-13
978-0-323-88616-1 (9780323886161)
Schweitzer Klassifikation
1. IntroductionYeliz Karaca and Dumitru Baleanu2. Theory of Complexity, Origin and Complex SystemsYeliz Karaca3. Multi-chaos, Fractal and Multi-fractional AI in Different Complex SystemsYeliz Karaca4. High Performance Computing and Computational Intelligence Applications with Multi-Chaos PerspectiveOsvaldo Gervasi, Damiano Perri, Marco Simonetti, and Sergio Tasso5. Human Hypercomplexity: Error and Unpredictability in Complex Multi-Chaotic Social SystemsPiero Dominici Sr.6. Multifractal Complexity Analysis-based Dynamic Media Text Categorization Models by Natural Language Processing with BERTYeliz Karaca, Yu-Dong Zhang, Ahu Dereli Dursun, and Shui-Hua Wang7. Mittag-Leffler Functions with Heavy-tailed Distributions' Algorithm based on Different Biology Datasets to be Fit for Optimum Mathematical Models' StrategiesDumitru Baleanu and Yeliz Karaca8. Artificial Neural Network Modeling of Systems Biology Datasets Fit Based on Mittag-Leffler Functions with Heavy-tailed Distributions for Diagnostic and Predictive Precision MedicineYeliz Karaca and Dumitru Baleanu9. Computational Fractional-Order Calculus and Classical Calculus AI for Comparative Differentiability Prediction Analyses of Complex-systems-grounded ParadigmYeliz Karaca and Dumitru Baleanu10. Pattern Formation Induced by Fractional-order Diffusive Model of COVID-19Yeliz Karaca and Naveed Iqbal11. Prony's series in time and frequency domains and relevant fractional modelsJordan Hristov12. A chain of kinetic equations of Bogoliubov-Born-Green-Kirkwood-Yvon and its application to non-equilibrium complex systemsMukhayo Rasulova V, Tohir Vohidovich Akramov, Nicolai (Jr) Bogoliubov, and Umarbek Avazov13. Hearing Loss Detection in Complex Setting by Stationary Wavelet Rényi Entropy and Three-Segment Biogeography-Based OptimizationYabei Li, Junding Sun, and Chong Yao14. Shannon Entropy-based Complexity Quantification of Nonlinear Stochastic Process: Diagnostic and Predictive Spatio-temporal Uncertainty of Multiple Sclerosis SubgroupsYeliz Karaca, and Majaz Moonis15. Chest X-ray image detection for pneumonia via complex convolutional neural network and Biogeography-based optimizationJunding Sun, Xiang Li, and Mengyao Zhai16. Complex facial expression recognition via Densenet-121Bin Li17. 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 Nolè18. Managing Information Security risk and Internet of Things (IoT) Impact on Challenges of Medicinal Problems with Complex Settings: A Complete Systematic ApproachN. Thirupathi Rao, Debnath Bhattacharyya, and Eali Stephen Neal Joshua19. An Extensive Discussion on Utilization of Data Security and Big Data Models for Resolving Healthcare ProblemsN. Thirupathi Rao, Debnath Bhattacharyya, and Eali Stephen Neal Joshua
