APPROACHES TO THE REDUCTION OF ERRORS IN THE CALCULATION OF MATHEMATICAL MODELS OF COMBAT ACTIONS IN COMPUTER SIMULATION SYSTEMS
DOI:
https://doi.org/10.17721/2519-481X/2024/84-12Keywords:
simulation modeling systems, floating-point binary number calculation accuracy, improving the accuracy of simulation modeling systems, combat simulation modeling systemsAbstract
The scientific article is dedicated to the study and analysis of modern methods for reducing errors in numerical calculations, which are critically important for enhancing the accuracy and reliability of simulation models of combat operations. Several approaches have been investigated that can be applied to achieve this goal.
The first method discussed is the fourth-order Runge-Kutta method, which is one of the most common methods for numerically solving differential equations. This method allows for high accuracy of solutions with a relatively small number of calculations, making it effective for real-time use in computer simulation systems.
The second approach considered in the article is the use of the Kahan algorithm for precise summation. The Kahan algorithm significantly reduces errors that occur when summing a large number of floating-point numbers, which is particularly relevant in cases where large volumes of data need to be processed with high precision.
Additionally, the article discusses the application of high-precision arithmetic, which allows calculations to be performed with more significant digits than is possible with standard floating-point data types. This is achieved by representing numbers as arrays, allowing for the storage and processing of additional bits of precision.
All the mentioned approaches are implemented in the Python programming language, ensuring their accessibility and ease of integration into existing simulation systems. Python, with its simplicity and wide range of libraries for scientific computing, is an ideal choice for implementing such algorithms.
Thus, the article provides a comprehensive overview of methods for reducing errors in numerical calculations that can be applied to improve the accuracy of mathematical models of combat operations. The proposed approaches can be useful for developers of simulation systems who aim to enhance the accuracy and reliability of
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