Abstract
This study focuses on integrating mathematical and statistical modeling, where a statistical model estimates the parameters of a mathematical model, or a mathematical model generates data to train a statistical model. This integration benefits both approaches: mathematical models improve the accuracy of statistical models, while statistical models help reduce bias in mathematical ones. The findings demonstrate that this combination is a valuable tool for understanding and predicting dynamic systems, offering more accurate and flexible models. Research consistently shows that integrating these models is an ideal approach for solving complex problems and understanding various systems.
| Original language | English |
|---|---|
| Pages (from-to) | 175-189 |
| Number of pages | 15 |
| Journal | Journal of Mechanics of Continua and Mathematical Sciences |
| Volume | 19 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2024 |
Keywords
- Complex problem
- Mathematical Modeling
- Statistical Modeling Sustainability
- Ultimately Indicated
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