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Herausgeber: 
  • Yu-Dong (Professor, Department of Informatics, Uni
  • Dumitru (Professor, Institute of Space Sciences, M
  • Yeliz (Assistant Professor of Applied Mathematics
  • Osvaldo (Professor, Department of Mathematics and
  • Majaz (Professor of Neurology and Psychiatry and D
  • Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Juni 2022  
    Genre:  Naturwissensch., Medizin, Technik 
    ISBN:  9780323900324 
    EAN-Code: 
    9780323900324 
    Verlag:  Elsevier Science & Technology 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 276 mm / B 216 mm / D 0 mm 
    Gewicht:  450 gr 
    Seiten:  350 
    Illustration:  70 illustrations (20 in full color); Illustrations, unspecified 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    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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