REGRESSION MODEL OF SPACE OF HEAT COMFORT STATES

Abstract

Modeling the hyperspace of system states by the method of regression analysis, mathematical analysis of regression equations that model the thermal comfort index, optimization of thermal comfort by determining the coordinates of the projection of the vector image of thermal comfort onto a state hyperplane and solving an equation with many variables. Development of methods and models for a formal description of the space of states of human thermal comfort. The use of the method of regression analysis as a tool for modeling the state of thermal comfort in multidimensional hyperspace of system states is investigated. The procedure for calculating the PMV thermal comfort index and the formation of control commands for ACS of the thermal environment have been simplified. It is proved that a linear and quasilinear model of the state surface of the TC system within the selected TC intervals with sufficient accuracy for practical use calculates the PMV thermal comfort index. The regression analysis method is developed and extended to the class of thermal comfort systems. For the first time, a formal model of the space of states of thermal comfort is represented by linear and quasilinear polynomials. The state model of a complex multifactor system for providing thermal comfort for a person is represented by regression polynomials in a linear and quasilinear form, which greatly simplifies the calculation of the PMV index, classification of the state of thermal comfort, the search for optimal operating modes and command formation for actuators that are part of the ACS of the TC.