Study of modeling problems in controlling the operating modes of a benzene production plant under conditions of fuzzy initial information
Batyr Orazbayev Yerlan Izbassarov Oğuz Findik Lyailya K urmangaziyeva
AbstractThis article discusses the study and analysis of modeling methods for controlling the operating modes of a benzene production plant under conditions of uncertainty of initial information. The implementation of methods for visualizing fuzzy logical inference based on mathematical models using the Python programming language is presented. The obtained results can be useful for improving the efficiency of the installation and minimizing the risks associated with inaccuracy of input parameters.