Special Session #12

Machine Learning and Computational Methods in Climatology, Earth and Environmental Sciences

 

Chair:

Prof. Zafer Aslan, Istanbul Aydın University, Department of Computer Science, Istanbul, Türkiye;  e-mail: zaferaslan@aydin.edu.tr

Co-Chairs:

Prof. Mete Tayanç, Marmara University, Faculty of Engineering, Department of Environmental Engineering, Istanbul, Türkiye; e-mail: mtayanc@marmara.edu.tr

Prof. Osman Uçan, Altınbaş University, Department of Electrical And Electronic Engineering, Istanbul, Türkiye; e-mail: osman.ucan@altinbas.edu.tr


Computational methods and tools along with modeling approaches as well as statistical analysis methods can ensure the exploration of different environmental processes, ecologies and habitats. Moreover, the significance of environmental impact assessments lies in their enabling of the formulation of controls and means of mitigating the impacts and communicating them to the public. This vital process does not only determine various possible environmental effects but also ensures the consideration of environmental factors toward informed decision-making, problem-solving and accurate predictions.

Based on these significant points and structure of environmental problems, our special session aims to enable the discussion of examples of successful applications of computational approaches in environmental sciences and other related fields, with a focus on the practical aspects of the applications to implement more accurate and reliable predictions, sustainability, modeling and simulations.

The topics include but are not limited to:

  • Wavelet and applications in climatology / environmental sciences, etc.
  • Machine learning methods
  • Computational techniques in environmental and / or atmospheric sciences
  • Statistical methods in earth sciences
  • Data mining and environmental statistics
  • Renewable energy sources
  • Computation and analytics on energy and environment
  • Hydrological modeling, water quality and balance
  • Soil and water conservation 
  • Hyperconnected ecosystems, resilience and sustainability
  • Pollution modeling and control
  • Epidemiology and/or health events
  • Climate change and agriculture
  • Environmental analysis, modeling and simulations
  • Meteorology and environmental engineering
  • Air pollution, prediction and control 
  • Digitizing climate action
  • Control theory, engineering and technology
  • Modeling of severe weather conditions and early warning systems
  • Risk factor identification and quantification
  • Machine learning applications in climatology/earth/environmental sciences