Author:
Tsapaev A A,Gumerov F M,Mazanov S V,Kharitonova O S,Bronskaya V V
Abstract
Abstract
In order to create a complex of control and prediction of optimal reaction conditions with a minimum value of chemical oxygen demand, a neural network model of supercritical water oxidation of industrial effluent water utilization process of hydroperoxide epoxidation of propylene at PJSC “Nizhnekamskneftekhim” was created. A full application Windows Forms, which implemented functions of loading a training sample from a file, setting the necessary training accuracy, entering a vector for obtaining results of neural network operation and graph plotting, was created.
Subject
General Physics and Astronomy
Cited by
3 articles.
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1. Experimental study of the production of composite particles of Co3O4/aluminum oxides in the processes of sub- and supercritical water oxidation;Case Studies in Chemical and Environmental Engineering;2023-12
2. Determination of the rational diameter of the pipeline using the neural network model;PROCEEDINGS OF THE II INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS, SYSTEMS AND TECHNOLOGIES: (CAMSTech-II 2021);2022
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