ABOUT THE INTERNATIONAL CONFERENCE:
Nonlinear Complex Systems: The branch of mathematics and physics deals with systems governed by nonlinear equations or laws. Nonlinear dynamical systems exhibit complex behavior and are often characterized by sensitivity to initial conditions and the emergence of chaotic patterns. The field finds applications in various disciplines, including engineering, biology, economics, and more.
The conference highlights the study of systems displaying nonlinear behavior, leading to intricate dynamics. Nonlinear systems are characterized by interactions and relationships among components that do not adhere to simple linear patterns, making their behavior challenging to predict and comprehend.
Computational Intelligence: An area of artificial intelligence (AI) aiming to develop algorithms and models inspired by human intelligence and cognitive processes. It encompasses various techniques such as neural networks, genetic algorithms, fuzzy logic, and swarm intelligence. Computational intelligence is employed to solve complex problems and make intelligent decisions across diverse domains. The conference likely emphasizes the application of computational techniques and intelligent algorithms to address complex issues within the context of nonlinear systems. Computational intelligence utilizes AI, machine learning, and other advanced computational methods to analyze, model, and predict behavior within complex systems, which may be challenging to analyze using traditional approaches.
The combination of these two fields in an international conference suggests an interdisciplinary event where researchers, academics, and practitioners converge to share research findings, exchange ideas, and discuss advancements in both Nonlinear Complex Systems and Computational Intelligence. This synthesis encourages a collaborative environment that bridges mathematical intricacies and AI-driven solutions to real-world challenges.
This conference will focus on:
- Nonlinear systems and their complex nature
- Chaos and synchronization
- Numerical analysis and the development of algorithms for simulation
- Scientific computing and their applications
- Machine and deep learning
- Data driven model
- Fluid dynamics
- Fuzzy inference system
- Mathematical biological model