Advanced computational and mathematical models effectively enable the investigation of complexities, entailing the application of optimal analytical methods for a precise definition of the problems based on mathematics, computing and controllable experimentation. This sophisticated approach accompanied by data-intensive applications making exhaustive usage of data in all the possible heterogeneous forms profoundly allows us to test the related solutions and attain accurate decision-making before the employment of expansive resources. Thereafter, this mode of approach becomes more prominent in complex systems to obtain global and robust solutions optimized by integrative and multifarious methods, mathematics-informed techniques, optimization processes, computer-assisted processes, numerical simulations and technical analyses along with their related applications. In view of these, new pathways can be opened up and a bridge to the novel attempts of research can be provided for demonstrating the significance of advanced computational and mathematical models for the investigation of complex systems, merging interdisciplinary perspectives toward paving the way for innovative research, thought-provoking deliberations and fruitful shared experiences.
Based on these considerations, modes and techniques, the following topics can be further looked into and researched:
- Fractal and/or fractional calculus
- Fractal Artificial Intelligence (Fractal AI)
- Fractional-order systems
- Computational imaging and simulation technologies in biomedicine
- Computational modeling of medical complex systems
- Intelligence-based models in image and / or signal processing
- AI and machine learning applications in complex systems
- High-performance computing
- Integrative machine-learning and neuroscience
- Data-driven computing
- Data-intensive applications
- Data analytics-based models
- Differentiability in differential equations with big data applications
- Fractional order differential, integral equations and systems
- Fractional computing modeling and systems
- Multifractal analysis
- Entropy and its applications
- Wavelet and its applications
- Wavelet analysis and synthesis
- Entropy of complex dynamics, processes and systems
- Computational applied sciences
- Control and dynamics of multi-agent network systems
- Bifurcation and chaos in complex systems
- Computational complexity
- Fractional-calculus-based control scheme for uncertain dynamical systems
- Computational intelligence-based methodologies and techniques
- Mathematical analysis and modeling in complex systems
- Fractional mathematical modeling with computational complexity
- Mathematical modeling and Artificial Intelligence (AI) in complex systems
- Convolutional neural networks with fractional order gradient method
- Fractional calculus with deep neural networks
- Quantum computation and optimization models of complex systems
- Fuzzy fractional calculus with applications
- Quantum artificial intelligence (QAI)
- Quantum fractals
- Dynamical behaviors and their types
- Stochastic gene expression
- Systems of coupled cells
- Efficient and stable training of differential equations
- Constitutive models with neural networks
- Dynamics of multi-agent network systems
- PDEs for image/signal and data processing
- Computational science and mathematical modeling (machine learning, big data and algorithms, and so forth)
Besides the many other related points with mathematical, numerical and computational modeling.
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