Scope:
The workshop is specifically focusing on algorithms and methodologies inspired by the intricate dynamics of forest ecosystems. Forests, with their complex interplay of growth, competition, and adaptation, offer a rich source of inspiration for computational models. The workshop aims to provide a holistic understanding of forest-inspired computational intelligence, bridging the gap between the natural world's wonders and their application in solving complex computational problems.
The scientific scope of this workshop encompasses:
- An exploration of the core tenets of computational intelligence, including evolutionary algorithms, swarm intelligence, and neural networks, setting the stage for understanding forest-inspired methodologies.
- A comprehensive study of the structural and dynamic aspects of forests, emphasizing the processes that can be mirrored in computational models. This includes understanding how trees compete for resources, adapt to their environment, and grow over time.
- Detailed examination and discussion of algorithms like the Forest Optimization Algorithm (FOA) and the use of Random Forest as a classifier. Participants will gain insights into the mechanics of these algorithms, their strengths, and potential areas of improvement.
- Investigating the potential of combining FOA with other established algorithms to enhance performance and applicability. This segment will delve into the science behind creating effective hybrid models that leverage the best of multiple methodologies.
- A pragmatic look at how forest-inspired computational intelligence methods are being applied in various domains, from network design to medical diagnostics. Through case studies, participants will understand the practical implications and benefits of these algorithms.
- A forward-looking discussion on the potential advancements, challenges, and future directions of forest-inspired computational intelligence. This will involve both theoretical predictions and practical considerations for researchers and practitioners.
Topics:
Topics of interest include (but are not limited to):
- Understanding Forest Ecosystem Dynamics
- Forest-Based and Forest-Inspired optimization algorithms
- Hybrid Forest-inspired Models in Computational Intelligence
- Parameter Tuning in Forest-Inspired Algorithms
- Practical applications of forest-inspired algorithms
- Using forest-inspired algorithms for medical diagnostics, prognosis, and treatment planning.
- Evaluating forest-inspired algorithms against other nature-inspired algorithms, such as Particle Swarm Optimization or Genetic Algorithms.
- Scalability and Performance enhancement techniques to ensure forest-inspired algorithms can handle large datasets and complex problems efficiently.
- Forest-Inspired Algorithms in Finance for Applications in stock market prediction, risk assessment, and portfolio optimization.
- Emerging trends, and areas of research that will shape the next generation of forest-inspired algorithms.
Important Dates:
- Submission: Dec. 7, 2023
- Notification: Dec. 25, 2023
- Registration: Jan. 5, 2024
Workshop Submissions:
https://easychair.org/conferences/?conf=worldcistworkshops2024
Organizing Committee:
- Robertas Damaševičius, Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland,
This email address is being protected from spambots. You need JavaScript enabled to view it. - Rytis Maskeliunas, Department of Multimedia Technologies, Kaunas University of Technology, Kaunas, Lithuania,
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Program Committee:
- Andre Schekelmann,
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