The theory of complexity enables the problems to be classified based on the difficulty with which they can be solved by means of the employment of algorithms. Novel computational methods with complex data and recent advancements regarding data analytics from the complex systems perspective need to be handled for a versatile understanding of huge amounts of data to enable predictive enhancements through the transfer of the results based on data analytics to general benefits, which underpins the utility and interdisciplinary approach of the domain. Models are important in that they probe the understanding of what can be learned from simulations which can serve multiple purposes such as checking the understanding of the past, optimizing the present, predicting the future if the present is known and estimating the future if one guesses the present. This direction explains what is seen and transforms data into meaning.
Complexity theory is a related component for complex systems in modern science with no precise boundaries or exact definition in fact. With the portrayal of different ways, as general systems theory (GST), the grand theory, and complex adaptive systems (CAS), systems theory, there exists the umbrella term [Karaca, Y. (2022)]. Complexity theory is under the process of becoming a science which acknowledges the creativity lying in the nature. By opening a new way of seeing the world and realizing the complex dynamic systems with their components being sensitive to initial conditions and having emergent properties, it becomes possible to navigate carefully with respect to complex systems on which the quality of our lives depends, ranging from the microbial ecosystems to biosphere. As we have impact on such systems, it may be thought we may be in control of them, but the instances are different.
Complexity becomes further complicated when which aspects of system-environment interaction are modeled by chaos. Another different feature of it is that while the study of complex systems addresses both the dynamics and structure of the structure, chaos, which signifies randomness and disorder, deals with a few parameters and the dynamics of their values. Randomness and disorder are also included in the study of complex systems and the concept of a chaotic environment can be replaced with complex environment due to the fact that complex refers to both randomness of disorder and also deterministic chaos [Bar-Yam, Y. et al. (1998)], [Karaca, Y. (2022)]. Complexity theory is a transdisciplinary systems theory dealing with change basically speaking [Ortega, L., & Han, Z. (Eds.), (2017)], and it is originated in mathematics and physical sciences besides being employed extensively in humanities and social sciences as well. In industrial, technical or organizational issues, a pattern inherent about complexity is also subtly poised between the pendulum order and chaos [Ladyman, J. et al. (2013)]. Hence, the study of the complex system entails the studying of the behavior of the whole so that the behavior of the parts of the system can be explained accurately and thoroughly [Gharajedaghi, J. (2011)]. Laws of complexity have their inherent hierarchical scales that are universal with properties of being scalar and having self-similarity, which hints that an object is made up of subparts across multiple levels alike the whole object's structure. Self-organizing and adaptive behaviors of living systems also demonstrate the ways order emerges within complex adaptive systems. The intensity through which interactions take place in the system signifies if the systems are close to equilibrium or not. The system may be open to change and can be restructured towards high levels of complexity like the differentiation of subsystems, which does not always necessitate turbulence, disorder or returning back to stability [Karaca, Y. (2022)].
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