International Journal of Electrical and Power Engineering
ISSN: Online 1993-6001ISSN: Print 1990-7958
Abstract
Complex systems are usually represented by structurally invariant models acquiring their characteristic properties in simulations. This approach assumes and infers idealized simplifications to models these systems. We consider this standard approach as omitting crucial features of phenomenological interaction mechanisms related to processes of emergence of such complex systems. We consider, as the main feature, the quasiness of the structural dynamics that generate complex systems. Generation achieved through prevalently coherent sequences and combinations of interactions. Quasiness (dynamics of loss and recovery, in homogeneity, multiplicity, non-regularity, and partiality) represents the incompleteness of the interaction mechanisms. Complex systems possess local coherences corresponding to the phenomenological complexity. Complex systems are considered quasi-systems, not always systems, not always the same system, and not only systems. We address problems of representing the quasiness of coherence (quasi-coherence) such as the ability to recover and tolerate temporary levels of incoherence. The main results of the study focus on modelling quasi-coherence through the changing of rules in models of emergence. This is in contrast to models of fixed structural rules allowing only parametrical variations. We present a version of standard analytical approach compatible with quasiness of systemic emergence and related mathematical issues. The same approach is considered for networks, artificial neural networks and we introduce the concept of quasification for fixed models. Finally, we assert that suitable representations of structural dynamics and its quasiness are needed to model, simulate, and adopt effective interventions on emergence of complex systems. In direct contrast to standard methods that only consider their properties.
How to cite this article:
Mustefa Jibril. On Modelling the Structural Quasiness of Complex Systems.
DOI: https://doi.org/10.36478/ijepe.2021.52.68
URL: https://www.makhillpublications.co/view-article/1990-7958/ijepe.2021.52.68