For tackling applied complexity, it becomes pivotal to fundamentally deal with the solution of complex problems characterized by nonlinearity, dynamic aspects, ambiguity, causality, uncertainty and transiency, to name some. Within this scope, each system requires optimal solutions peculiar to its inherent features and parameters. The dissipative structure surrounding complexity transforms into research and applications to understand the world and the universe, converting information into knowledge to create, maintain and expand the organized complexity of the systems. Motivated against this premise and transforming quality, requirement and background, it is important to keep abreast with up-to-date developments, findings, advances in theories, research, models, applications, analyses and simulations with technological advances in different respective realms. In addition, complex nonlinear thinking shows the imprint of nature principles with elements of open-ended knowledge systems, which encompasses not only pure and rationalized knowledge but also human intuition and convictions. In other words, this is an art of thinking which helps one gain ability to act in an efficient way in complex systems. It is possible to study a nonlinear complex system in different means, macroscopically (studying its behavior) or mesoscopically (studying the subsystems’ operation) and microscopically.
There exists still a compelling need in these areas since it seems that most work is based on traditional outlook focusing on one single domain. In fact, it should be devised to make plans to produce intends to bring together the related frontier theories and novel application techniques based on mathematical models, advanced computational models and top-notch technological progresses in different disciplines with completely different perspectives handling complex variables considering the ever-changing landscape and needs. The overarching modeling of various systems such as complex systems include but are not restricted to advancements, applications in Artificial Intelligence (AI) applications, machine learning methods, big data analysis, spatiotemporal scales, fractals and multifractional methods, fractional calculus, wavelet, entropy, quantum, dynamical processes concerning the fixed, variable and distributed systems, nonlinear dynamics and non-equilibrium processes, stochastic processes, fractional order integro-differentiation, hierarchical nonlinear principal component analyses and the other related topics. It is also important to be proficient in tackling different processes inherent in complex systems so that the provision of efficient, robust and global solutions can be ensured through a holistic perspective. At that point, it becomes vital to consider the particulars of the respective domain, multifarious methods, as different from the conventional perspectives. For all these reasons, it can be pointed out that there is much work to be conducted as there still exists a compelling need for integrative and resourceful schemes pointing towards a unified science framework.
Concerning complex systems and applied complexity, an interdisciplinary perspective is concerned with handling the solution of complex problems which are characterized by nonlinearity, dynamic aspects, ambiguity, causality, uncertainty and transiency, and so forth. Within this scope, each system requires optimal solutions peculiar to its inherent features and parameters. The dissipative structure surrounding complexity transforms into research and applications to understand the world and the universe converting information into knowledge to create, maintain and expand the organized complexity of the systems. Motivated against this premise and transforming quality, requirement and background, it is of pivotal significance that the most up-to-date developments, findings, advances in theories, research, models, applications, analyses and simulations with technological advances should be tracked in different respective realms.
Exact sciences, namely mathematics, physics, biology and chemistry, besides medicine, neurology, virology engineering, applied sciences, nanotechnology, bioinformatics, life sciences, computer science, economics, finance and social sciences within the scope of theories, research, models, applications, analyses, experimental observations and simulations can be analyzed by this perspective to serve the needs of different aspects of complexity from emergence by minimizing the complexity of the problems whose solutions are based on advanced mathematical foundations and corresponding algorithmic models, which constitute the applied aspect of complexity. This encompassing scope ranges from designing and to transformation in each domain in complex systems and nonlinear dynamics, with pure, natural and applied aspects to provide methodology, tools, means, applications, techniques, methodologies, research aspects and theories so that solutions for the current pressing challenges, which exceed the possible limits of human comprehension, can be found through these aforementioned means. With the presentation of such means, it will also be possible for individuals including researchers, academics and practitioners to be well equipped so that they can come up with applicable and timely generation and implementation of the robust and optimized actual solutions towards complex problems under uncertain, transient and dynamic complex systems with dissipative and nonlinear structures. As for meeting the needs of the era, the outlook summarized herein intends to enable us to generate a sequence of solutions that need the peculiar handling for each system, domain and matter under consideration. This feature with distinctive handling but at the same time margining means that for each discipline (engineering, applied sciences, life sciences, computational science, medicine, mathematics, exact sciences and social sciences, to name some), actionable, well-suited and tailored solutions need to be elaborated on, discussed, demonstrated and explained by taking into consideration the specific needs of each domain and application both theoretically, methodologically and practice-wise, considering the precise and to-the-point conveyance of relevant aspects.
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