Open AccessMethod for searching the extremum of multidimensional functions in solving engineering problems of machines for forestry works
Author(s) -
Liudmyla Titova,
Oleksandr Nadtochiy
Publication year - 2020
Publication title -
machinery and energetics
Language(s) - English
Resource type - Journals
eISSN - 2663-1342
pISSN - 2663-1334
DOI - 10.31548/machenergy2020.04.131
Subject(s) - implementation , computer science , process (computing) , mathematical optimization , gradient descent , basis (linear algebra) , algorithm , mathematics , machine learning , programming language , geometry , artificial neural network
This article is devoted to the analysis of the most common optimization methods used in practical engineering problems of finding the extremum of multidimensional functions and the formation on the basis of the identified properties of recommendations for choosing the best on different data sets. In the process of analysis, various implementations of gradient descent methods, pulse methods, adaptive methods and quasi-Newtonian methods were considered, and the advantages and problems of each of the methods in their use were summarized. Developed computer program that implements the use of all considered methods. The computational experiment performed for the three functions showed that the zero -Rosenbrock and zero - Powell methods proved to be the most effective.