The article discusses the integration of hybrid methods of system analysis to improve the efficiency of decision-making under uncertainty and multiparameter constraints. Modern approaches to solving complex control and optimization problems are analyzed. The use of hybrid algorithms that combine classical and modern analysis methods, such as genetic algorithms, the Monte Carlo method, and neural networks is proposed. The use of these models allows improving the accuracy and stability of decisions, as well as reducing time and computational costs. The article discusses modern approaches to the integration of hybrid methods of system analysis and optimization algorithms
| Mualliflar | Хасанова, Махинур, Atajanova, Saidaxon |
|---|---|
| Jurnal | Al-Farg'oniy avlodlari |
| Nashr sanasi | 2024-12-28 |
| Son | 4 |
| Betlar | 193-196 |
| Til | Rus |
systems analysis, hybrid methods, decision making, optimization, control, algorithms, uncertainty, multivariable systems, системный анализ, гибридные методы, принятие решений, оптимизация, управление, алгоритмы, неопределенность, многомерные системы
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