Major Role of Multiscale Entropy Evolution in Complex Systems and Data Science

Shahid Nawaz, Muhammad Saleem, Fedor V. Kusmartsev, Dalaver H. Anjum

    Research output: Contribution to journalArticlepeer-review

    1 Scopus citations

    Abstract

    Complex systems are prevalent in various disciplines encompassing the natural and social sciences, such as physics, biology, economics, and sociology. Leveraging data science techniques, particularly those rooted in artificial intelligence and machine learning, offers a promising avenue for comprehending the intricacies of complex systems without necessitating detailed knowledge of underlying dynamics. In this paper, we demonstrate that multiscale entropy (MSE) is pivotal in describing the steady state of complex systems. Introducing the multiscale entropy dynamics (MED) methodology, we provide a framework for dissecting system dynamics and uncovering the driving forces behind their evolution. Our investigation reveals that the MED methodology facilitates the expression of complex system dynamics through a Generalized Nonlinear Schrödinger Equation (GNSE) that thus demonstrates its potential applicability across diverse complex systems. By elucidating the entropic underpinnings of complexity, our study paves the way for a deeper understanding of dynamic phenomena. It offers insights into the behavior of complex systems across various domains.

    Original languageBritish English
    Article number330
    JournalEntropy
    Volume26
    Issue number4
    DOIs
    StatePublished - Apr 2024

    Keywords

    • complex system
    • data science
    • generalized nonlinear Schrödinger equation
    • multiscale entropy dynamics
    • quasiparticle

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