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Special Session #14
Mathematical Modeling, Wavelets and Engineering Applications in Earth and Nature Sciences for Real-World Phenomena
Chair:
Prof. Funda Dökmen,
Kocaeli University, Department of
Plant and Animal Production, Kocaeli, Türkiye; e-mail:
funda.dokmen@kocaeli.edu.tr
;
f_dokmen@hotmail.com
Co-Chair:
Prof. Emrah Tuncay Özdemir, İstanbul Technical University, Department of Meteorological Engineering
, Istanbul, Türkiye; e-mail:
etozdemir@itu.edu.tr
;
etozdemir@gmail.com
Mathematical modeling for dynamic systems is intricately connected to the examination of different meteorological conditions, climate change, natural and atmospheric science. A structured framework can be designed and implemented for the purposes of analyzing, predicting and understanding complex interactions occurring within Earth's atmosphere and climatic systems. Besides this, mathematical modeling converts the physical processes governing meteorological and atmospheric phenomena into equations and algorithms. These integrative models may represent critical aspects such as temperature, humidity, air pressure as well as wind patterns so that accurate forecasts of weather conditions and variations can be ensured. On the other hand, analyzing dynamic systems is important to understand how such variables evolve over time and interact across different scales along with understanding nonlinearities and feedback mechanisms in atmospheric processes, which are all crucial for improving prediction accuracy. In conjunction with enhancing understanding, advanced tools and techniques like artificial intelligence (AI), machine learning, numerical simulations, remote sensing and satellite, advanced computing, climate models, aerial vehicles, geographic information systems, renewable energy technologies, and so forth are highly effective and when applied to climate change, even more essential.
Wavelets as a powerful mathematical tool and their analyses are employed for studying time-series data which include climate variability and weather patterns. In the area of agriculture, wavelets, some uses of which are drought monitoring, rainfall analysis, crop yield prediction, can be utilized for analyzing and predicting seasonal and periodical variations in meteorological conditions to pave the way for better planning, finding optimal timing and ensuring environmental sustainability.
The integration of mathematical modeling and dynamic systems into Earth sciences, natural sciences, meteorology, aviation and atmospheric science drives the implementation of advanced and efficient applications in agriculture, irrigation, urban planning, risk mitigation, disaster management and renewable energy, among many others. Consequently, our special session aims to bridge theory and real-world applications in these related domains so that ideas, innovations, practice and research can contribute to protection of communities and fostering sustainable development while mitigating climate impacts and adapting to the changing environments.
The topics include but are not limited to:
Wavelets in atmospheric changes and weather patterns
Machine learning and AI applications in Earth sciences / climatology / life sciences / nature sciences, etc.
Mathematical modeling for life and natural sciences
Analysis of climate patterns by greenhouse gas emissions
Predicting future scenarios based on anthropogenic factors
Digital technologies and agrifood
Predictive algorithms for future climatic and / or atmospheric phenomena
Comparative analysis in nonlinear models
Modeling long-term nonrenewable energy production
Meteorological remote sensing
Environmental monitoring and assessment
Sensitivity analysis in environmental sciences
Wavelet transform models for parameters changes
Wavelet applications in epidemiology and ecology
Advanced statistical methods and models
Water management and its applications
Agricultural ecology, and its applications
Agricultural and its modeling applications
Mathematical modeling in nature sciences
Dynamical systems and atmospheric sciences
Aeronautical meteorology applications and atmospheric dynamic