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Why is it important?
Imitation models for computing the environmental water pollution level depending on the intensity of pollution sources created by the author over the years are presented. For this purpose, an additive model of a non-stationary random process is considered. For the modeling of its components, models that consider only dilution and self-purification processes are proposed for waste water and three-dimensional turbulent diffusion equations for river waters, and multidimensional Gaussian Markov series are proposed for modeling the random component. The purpose, the capabilities and the peculiarities of such imitation models are discussed taking into account the peculiarities of the water objects. The modular principle of creating imitation models is proposed to facilitate their development and use.
Perspectives
The described models were widely used in automated systems for controlling and managing the pollution of water objects, both in their creation and in operation, to solve many different problems, such as: making optimal decisions in the creation, testing and operation of automatic monitoring systems; when calculating the values of the pollution parameters at the uncontrolled points of the control environment object; to calculate the maximum allowable discharge for pollution sources in a dynamic mode taking into account the condition of the environmental object in the period under consideration; taking into account the pollution conditions and the possible variability of the condition of the control facility for the forecast of possible variability of the condition of the environmental object; for automatic detection of emergency pollutants in the conditions of their existence, etc.
Professor Kartlos Joseph Kachiashvili
Georgian Tachnical University
Read the Original
This page is a summary of: The Use of Imitation Models at Developing and Introducing Information-Control Systems, Journal of Software Engineering and Applications, January 2022, Scientific Research Publishing, Inc,,
DOI: 10.4236/jsea.2022.157014.
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