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Abstract
In this study, we focus on the accuracy of mathematical modeling of processes, regardless of selected observation results processing routines. This paper presents theoretical models of processes with assumptions fulfilled a priori and empirical models with unreliable original database and knowledge base. We consider applied problems of forecast and evaluation of target parameters, provisioning of grounds for optimal solutions based on theoretical and empirical models of processes. We introduce methods to design and evaluate the efficiency of model solutions which depend on the level of uncertainty while describing the processes of the object under study. Based on that, theoretical models and applied problems solved by their use are analyzed. Also, we discuss methods of reliability assumptions analysis and their control and techniques of information processing: the forecasting problem, the point estimation problem, the optimal solutions problem. In conclusion, some techniques based on interval estimates for developing empirical models of processes are presented.
Highlights
Акцентируется внимание на корректности математического моделирования процессов вне зависимости от выбранных процедур обработки результатов наблюдений
This paper presents theoretical models of processes with assumptions fulfilled a priori and empirical models with unreliable original database and knowledge base
We introduce methods to design and evaluate the efficiency of model solutions which depend on the level of uncertainty while describing the processes of the object under study
Summary
Акцентируется внимание на корректности математического моделирования процессов вне зависимости от выбранных процедур обработки результатов наблюдений. Рассматриваются прикладные задачи прогноза и оценки параметров, обоснования оптимальных решений, которые базируются на теоретических и эмпирических моделях процессов. Предлагаются методы конструирования и оценки работоспособности модельных решений, которые зависят от уровня неопределенности описания процессов исследуемого объекта.
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