Algorithms of Multifactorial Regression Modeling in Ecological and Hygienic Studies - Antonomov, M.Yu.; Shevchenko, A.A.; Kulagin, A.A. (Кибернетика и вычислительная техника, 2017)
Introduction. One of the most urgent problems of environmental health is soil contamination by oil and petroleum products (PP) and its impact on crop productivity and population health. The main task here is to determine the acceptable or safe concentrations of PP in the soil. However, at present time there is no unified approach of PP regulating in different countries. One possible solution of the problem is mathematical modeling of the results of experimental studies. With the help of mathematical models, it becomes possible not only to describe the investigated dependencies, but also to calculate safe levels of PP in the soil. The purpose of the paper is to develop a methodology for constructing and using multifactor nonlinear regression models from data obtained in a real ecological and biological experiment. Results. The article presents the results of an experimental study of the influence of one type of petroleum products — diesel fuel, when it enters the soil to germinate one of the most important crops — wheat. It is shown that the mathematical model describing the suppres sion of wheat growth should be a multifactorial function ("time — concentration — effect"), which has a nonlinear character. An algorithm for constructing multifactorial nonlinear regression models is proposed. On the basis of experimental data, an adequate multifactor nonlinear mathematical model was developed. This made it possible to calculate the threshold concentration of diesel fuel, which does not affect the growth of wheat. Conclusion. On the basis of the proposed algorithm from experimental data an adequate multifactor nonlinear regression model was constructed. With the help of this model, the concentration of diesel fuel that does not cause a negative effect on the growth of wheat was calculated.