The course "Special Topics in Mathematical Modeling" consists of two parts. The first part is dedicated to studying the modeling of complex socio-economic processes based on inductive modeling and combining different types of models, in particular biophysical models with methods of regression analysis, clustering, neural networks, the MSUA method, and others. The second part focuses on the study of principles, algorithms, and procedures for developing multi-physical and geometric computational software.

The aim of the course is to master the fundamental principles of mathematical modeling and acquire practical skills in applying the relevant tools.

Key topics covered in the first part:

1. The current state of approaches and methods for building inductive models

2. Modeling complex socio-economic processes using the inductive approach

3. Evolutionary computation in multidimensional optimization problems

4. Cluster analysis and its application to large volumes of data

5. Model quality assessment

6. Modeling of sustainable development indicators

7. Modeling of emergencies and their consequences